Sun Mar 1 13:41:52 EST 2026 cd /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02 setenv SUBJECTS_DIR /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer /hpc/packages/minerva-centos7/freesurfer/7.2.0/freesurfer/bin/recon-all -base sub-02 -tp sub-02_ses-01_t1_Dopamine -tp sub-02_ses-02_t1_Dopamine -all subjid sub-02 setenv SUBJECTS_DIR /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer FREESURFER_HOME /hpc/packages/minerva-centos7/freesurfer/7.2.0/freesurfer Actual FREESURFER_HOME /hpc/packages/minerva-centos7/freesurfer/7.2.0/freesurfer build-stamp.txt: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b Linux lh06c22 5.14.0-570.58.1.el9_6.x86_64 #1 SMP PREEMPT_DYNAMIC Fri Oct 31 13:55:05 UTC 2025 x86_64 x86_64 x86_64 GNU/Linux cputime unlimited filesize unlimited datasize unlimited stacksize unlimited coredumpsize unlimited memoryuse unlimited vmemoryuse unlimited descriptors 20000 memorylocked unlimited maxproc 6190547 maxlocks unlimited maxsignal 6190547 maxmessage 819200 maxnice 0 maxrtprio 0 maxrttime unlimited total used free shared buff/cache available Mem: 1.5Ti 98Gi 1.3Ti 4.7Gi 103Gi 1.4Ti Swap: 44Gi 2.1Gi 42Gi ######################################## program versions used 7.2.0 (freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b) 7.2.0 ProgramName: lta_convert ProgramArguments: lta_convert -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_and ProgramArguments: mri_and -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_annotation2label ProgramArguments: mri_annotation2label -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_aparc2aseg ProgramArguments: mri_aparc2aseg -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_surf2volseg ProgramArguments: mri_surf2volseg -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_binarize ProgramArguments: mri_binarize -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_ca_label ProgramArguments: mri_ca_label -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_ca_normalize ProgramArguments: mri_ca_normalize -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_ca_register ProgramArguments: mri_ca_register -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_cc ProgramArguments: mri_cc -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_compute_overlap ProgramArguments: mri_compute_overlap -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_compute_seg_overlap ProgramArguments: mri_compute_seg_overlap -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_concat ProgramArguments: mri_concat -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_concatenate_lta ProgramArguments: mri_concatenate_lta -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 mri_convert -all-info ProgramName: mri_convert ProgramArguments: mri_convert -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_diff ProgramArguments: mri_diff -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_edit_wm_with_aseg ProgramArguments: mri_edit_wm_with_aseg -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_em_register ProgramArguments: mri_em_register -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_fill ProgramArguments: mri_fill -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_fuse_segmentations ProgramArguments: mri_fuse_segmentations -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_fwhm ProgramArguments: mri_fwhm -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_gcut ProgramArguments: mri_gcut -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_info ProgramArguments: mri_info -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_label2label ProgramArguments: mri_label2label -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_label2vol ProgramArguments: mri_label2vol -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_log_likelihood ProgramArguments: mri_log_likelihood -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_mask ProgramArguments: mri_mask -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_matrix_multiply ProgramArguments: mri_matrix_multiply -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_normalize ProgramArguments: mri_normalize -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_normalize_tp2 ProgramArguments: mri_normalize_tp2 -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:52-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_or ProgramArguments: mri_or -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_relabel_hypointensities ProgramArguments: mri_relabel_hypointensities -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_relabel_nonwm_hypos ProgramArguments: mri_relabel_nonwm_hypos -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_remove_neck ProgramArguments: mri_remove_neck -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 7.2.0 ProgramName: mri_robust_register ProgramArguments: mri_robust_register -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 7.2.0 ProgramName: mri_robust_template ProgramArguments: mri_robust_template -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_anatomical_stats ProgramArguments: mris_anatomical_stats -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_ca_label ProgramArguments: mris_ca_label -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_calc ProgramArguments: mris_calc -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_convert ProgramArguments: mris_convert -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_curvature ProgramArguments: mris_curvature -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_curvature_stats ProgramArguments: mris_curvature_stats -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_diff ProgramArguments: mris_diff -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_divide_parcellation ProgramArguments: mris_divide_parcellation -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_segment ProgramArguments: mri_segment -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_segstats ProgramArguments: mri_segstats -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_euler_number ProgramArguments: mris_euler_number -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_fix_topology ProgramArguments: mris_fix_topology -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_topo_fixer ProgramArguments: mris_topo_fixer -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_jacobian ProgramArguments: mris_jacobian -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_label2annot ProgramArguments: mris_label2annot -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_left_right_register ProgramArguments: mris_left_right_register -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_place_surface ProgramArguments: mris_place_surface -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mrisp_paint ProgramArguments: mrisp_paint -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_register ProgramArguments: mris_register -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_smooth ProgramArguments: mris_smooth -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_sphere ProgramArguments: mris_sphere -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_surface_stats ProgramArguments: mris_surface_stats -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_stats2seg ProgramArguments: mri_stats2seg -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_thickness ProgramArguments: mris_thickness -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_thickness_diff ProgramArguments: mris_thickness_diff -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_topo_fixer ProgramArguments: mris_topo_fixer -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_surf2surf ProgramArguments: mri_surf2surf -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_surf2vol ProgramArguments: mri_surf2vol -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_surfcluster ProgramArguments: mri_surfcluster -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mris_volmask ProgramArguments: mris_volmask -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_tessellate ProgramArguments: mri_tessellate -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_vol2surf ProgramArguments: mri_vol2surf -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_vol2vol ProgramArguments: mri_vol2vol -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_voldiff ProgramArguments: mri_voldiff -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: mri_watershed ProgramArguments: mri_watershed -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 ProgramName: tkregister2 ProgramArguments: tkregister2_cmdl -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 mri_motion_correct.fsl 7.2.0 mri_convert -all-info ProgramName: mri_convert ProgramArguments: mri_convert -all-info ProgramVersion: 7.2.0 TimeStamp: 2026/03/01-18:41:53-GMT BuildTime: Jul 20 2021 18:45:50 BuildStamp: freesurfer-linux-centos7_x86_64-7.2.0-20210720-aa8f76b User: walesr01 Machine: lh06c22 Platform: Linux PlatformVersion: 5.14.0-570.58.1.el9_6.x86_64 CompilerName: GCC CompilerVersion: 4.8.5 Program nu_correct, built from: Package MNI N3, version 1.12.0, compiled by nicks@terrier (x86_64-unknown-linux-gnu) on 2015-06-19 at 01:25:34 ####################################### GCADIR /hpc/packages/minerva-centos7/freesurfer/7.2.0/freesurfer/average GCA RB_all_2020-01-02.gca GCASkull RB_all_withskull_2020_01_02.gca AvgCurvTif folding.atlas.acfb40.noaparc.i12.2016-08-02.tif GCSDIR /hpc/packages/minerva-centos7/freesurfer/7.2.0/freesurfer/average GCS DKaparc.atlas.acfb40.noaparc.i12.2016-08-02.gcs ####################################### #-------------------------------------------- #@# Longitudinal Base Subject Creation Sun Mar 1 13:41:53 EST 2026 /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02 #-------------------------------------------- #@# Longitudinal Base Subject Creation Sun Mar 1 13:41:53 EST 2026 /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02 mri_diff --notallow-pix --notallow-geo /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-02_t1_Dopamine/mri/rawavg.mgz /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-01_t1_Dopamine/mri/rawavg.mgz @#@FSTIME 2026:03:01:13:41:53 mri_diff N 4 e 0.61 S 0.02 U 0.50 P 85% M 52044 F 0 R 1598 W 0 c 1 w 14 I 0 O 0 L 0.02 0.05 0.12 @#@FSLOADPOST 2026:03:01:13:41:54 mri_diff N 4 0.02 0.05 0.12 mri_robust_template --mov /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-01_t1_Dopamine/mri/norm.mgz /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-02_t1_Dopamine/mri/norm.mgz --lta /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/transforms/sub-02_ses-01_t1_Dopamine_to_sub-02.lta /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/transforms/sub-02_ses-02_t1_Dopamine_to_sub-02.lta --template /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/norm_template.mgz --average 1 --sat 4.685 7.2.0 --mov: Using /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-01_t1_Dopamine/mri/norm.mgz as movable/source volume. --mov: Using /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-02_t1_Dopamine/mri/norm.mgz as movable/source volume. Total: 2 input volumes --lta: Will output LTA transforms --template: Using /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/norm_template.mgz as template output volume. --average: Using method 1 for template computation. --sat: Using saturation 4.685 in M-estimator! reading source '/sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-01_t1_Dopamine/mri/norm.mgz'... converting source '/sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-01_t1_Dopamine/mri/norm.mgz' to bspline ... MRItoBSpline degree 3 reading source '/sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-02_t1_Dopamine/mri/norm.mgz'... converting source '/sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-02_t1_Dopamine/mri/norm.mgz' to bspline ... MRItoBSpline degree 3 Will use TP 2 as random initial target (seed 11916 ). MultiRegistration::initializing Xforms (init 2 , maxres 0 , iterate 5 , epsit 0.01 ) : [init] ========================= TP 1 to TP 2 ============================== Register TP 1 ( /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-01_t1_Dopamine/mri/norm.mgz ) to TP 2 ( /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-02_t1_Dopamine/mri/norm.mgz ) Input rotation's max deviation from rotation is: 1.68587e-07 computing mean coord of TP 2 ( /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-02_t1_Dopamine/mri/norm.mgz ) mapping back to rot, err = 0 computing mean coord of TP 1 ( /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-01_t1_Dopamine/mri/norm.mgz ) mapping back to rot, err = 8.42937e-08 mapping movs and creating initial template... using median -- Template : (1, 1, 1)mm and (256, 256, 256) voxels. Writing final template: /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/norm_template.mgz Writing final transforms (warps etc.)... Determinant( lta[ 0 ]) : 1 Determinant( lta[ 1 ]) : 1 registration took 0 minutes and 38 seconds. Thank you for using RobustTemplate! If you find it useful and use it for a publication, please cite: Within-Subject Template Estimation for Unbiased Longitudinal Image Analysis M. Reuter, N.J. Schmansky, H.D. Rosas, B. Fischl. NeuroImage 2012. http://dx.doi.org/10.1016/j.neuroimage.2012.02.084 http://reuter.mit.edu/papers/reuter-long12.pdf @#@FSTIME 2026:03:01:13:41:54 mri_robust_template N 12 e 38.27 S 0.61 U 37.46 P 99% M 891036 F 0 R 61052 W 0 c 54 w 26 I 0 O 0 L 0.02 0.05 0.12 @#@FSLOADPOST 2026:03:01:13:42:32 mri_robust_template N 12 0.50 0.17 0.16 mri_robust_template --mov /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-01_t1_Dopamine/mri/orig.mgz /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-02_t1_Dopamine/mri/orig.mgz --average 1 --ixforms /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/transforms/sub-02_ses-01_t1_Dopamine_to_sub-02.lta /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/transforms/sub-02_ses-02_t1_Dopamine_to_sub-02.lta --noit --template /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/orig.mgz 7.2.0 --mov: Using /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-01_t1_Dopamine/mri/orig.mgz as movable/source volume. --mov: Using /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-02_t1_Dopamine/mri/orig.mgz as movable/source volume. Total: 2 input volumes --average: Using method 1 for template computation. --ixforms: Will use init XFORMS. --noit: Will output only first template (no iterations)! --template: Using /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/orig.mgz as template output volume. reading source '/sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-01_t1_Dopamine/mri/orig.mgz'... converting source '/sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-01_t1_Dopamine/mri/orig.mgz' to bspline ... MRItoBSpline degree 3 reading source '/sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-02_t1_Dopamine/mri/orig.mgz'... converting source '/sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-02_t1_Dopamine/mri/orig.mgz' to bspline ... MRItoBSpline degree 3 mapping movs and creating initial template... using median -- Template : (1, 1, 1)mm and (256, 256, 256) voxels. Writing final template: /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/orig.mgz Writing final transforms (warps etc.)... registration took 0 minutes and 19 seconds. Thank you for using RobustTemplate! If you find it useful and use it for a publication, please cite: Within-Subject Template Estimation for Unbiased Longitudinal Image Analysis M. Reuter, N.J. Schmansky, H.D. Rosas, B. Fischl. NeuroImage 2012. http://dx.doi.org/10.1016/j.neuroimage.2012.02.084 http://reuter.mit.edu/papers/reuter-long12.pdf @#@FSTIME 2026:03:01:13:42:32 mri_robust_template N 11 e 18.56 S 0.05 U 18.38 P 99% M 223412 F 0 R 5131 W 0 c 22 w 16 I 0 O 0 L 0.50 0.17 0.16 @#@FSLOADPOST 2026:03:01:13:42:51 mri_robust_template N 11 0.64 0.22 0.18 /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/transforms mri_concatenate_lta -invert1 sub-02_ses-01_t1_Dopamine_to_sub-02.lta identity.nofile sub-02_to_sub-02_ses-01_t1_Dopamine.lta invert the first LTA before applying it Read individual LTAs Writing LTA to file sub-02_to_sub-02_ses-01_t1_Dopamine.lta... mri_concatenate_lta successful. @#@FSTIME 2026:03:01:13:42:51 mri_concatenate_lta N 4 e 0.00 S 0.00 U 0.00 P 80% M 4992 F 0 R 229 W 0 c 0 w 4 I 0 O 0 L 0.64 0.22 0.18 @#@FSLOADPOST 2026:03:01:13:42:51 mri_concatenate_lta N 4 0.64 0.22 0.18 mri_concatenate_lta -invert1 sub-02_ses-02_t1_Dopamine_to_sub-02.lta identity.nofile sub-02_to_sub-02_ses-02_t1_Dopamine.lta invert the first LTA before applying it Read individual LTAs Writing LTA to file sub-02_to_sub-02_ses-02_t1_Dopamine.lta... mri_concatenate_lta successful. @#@FSTIME 2026:03:01:13:42:51 mri_concatenate_lta N 4 e 0.00 S 0.00 U 0.00 P 80% M 4608 F 0 R 230 W 0 c 0 w 4 I 0 O 0 L 0.64 0.22 0.18 @#@FSLOADPOST 2026:03:01:13:42:51 mri_concatenate_lta N 4 0.64 0.22 0.18 mri_robust_template --mov /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-01_t1_Dopamine/mri/brainmask.mgz /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-02_t1_Dopamine/mri/brainmask.mgz --average 0 --ixforms /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/transforms/sub-02_ses-01_t1_Dopamine_to_sub-02.lta /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/transforms/sub-02_ses-02_t1_Dopamine_to_sub-02.lta --noit --finalnearest --template /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/brainmask_template.mgz 7.2.0 --mov: Using /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-01_t1_Dopamine/mri/brainmask.mgz as movable/source volume. --mov: Using /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-02_t1_Dopamine/mri/brainmask.mgz as movable/source volume. Total: 2 input volumes --average: Using method 0 for template computation. --ixforms: Will use init XFORMS. --noit: Will output only first template (no iterations)! --finalnearest: Use nearest neighbor interpolation for final average! --template: Using /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/brainmask_template.mgz as template output volume. reading source '/sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-01_t1_Dopamine/mri/brainmask.mgz'... converting source '/sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-01_t1_Dopamine/mri/brainmask.mgz' to bspline ... MRItoBSpline degree 3 reading source '/sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-02_t1_Dopamine/mri/brainmask.mgz'... converting source '/sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02_ses-02_t1_Dopamine/mri/brainmask.mgz' to bspline ... MRItoBSpline degree 3 mapping movs and creating initial template... using mean -- Template : (1, 1, 1)mm and (256, 256, 256) voxels. Writing final template: /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/brainmask_template.mgz Writing final transforms (warps etc.)... registration took 0 minutes and 8 seconds. Thank you for using RobustTemplate! If you find it useful and use it for a publication, please cite: Within-Subject Template Estimation for Unbiased Longitudinal Image Analysis M. Reuter, N.J. Schmansky, H.D. Rosas, B. Fischl. NeuroImage 2012. http://dx.doi.org/10.1016/j.neuroimage.2012.02.084 http://reuter.mit.edu/papers/reuter-long12.pdf @#@FSTIME 2026:03:01:13:42:51 mri_robust_template N 12 e 7.89 S 0.06 U 7.75 P 99% M 223688 F 0 R 9179 W 0 c 18 w 17 I 0 O 0 L 0.64 0.22 0.18 @#@FSLOADPOST 2026:03:01:13:42:59 mri_robust_template N 12 0.67 0.24 0.18 Started at Sun Mar 1 13:41:53 EST 2026 Ended at Sun Mar 1 13:42:59 EST 2026 rca-base-init Done #-------------------------------------------- #@# MotionCor Sun Mar 1 13:42:59 EST 2026 mri_add_xform_to_header -c /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/transforms/talairach.xfm /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/orig.mgz /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/orig.mgz INFO: extension is mgz @#@FSTIME 2026:03:01:13:42:59 mri_add_xform_to_header N 4 e 0.86 S 0.01 U 0.84 P 99% M 23032 F 0 R 1001 W 0 c 2 w 8 I 0 O 0 L 0.67 0.24 0.18 @#@FSLOADPOST 2026:03:01:13:43:00 mri_add_xform_to_header N 4 0.70 0.25 0.19 #-------------------------------------------- #@# Talairach Sun Mar 1 13:43:00 EST 2026 /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri mri_nu_correct.mni --no-rescale --i orig.mgz --o orig_nu.mgz --ants-n4 --n 1 --proto-iters 1000 --distance 50 /usr/bin/bc /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri /hpc/packages/minerva-centos7/freesurfer/7.2.0/freesurfer/bin/mri_nu_correct.mni --no-rescale --i orig.mgz --o orig_nu.mgz --ants-n4 --n 1 --proto-iters 1000 --distance 50 nIters 1 mri_nu_correct.mni 7.2.0 Linux lh06c22 5.14.0-570.58.1.el9_6.x86_64 #1 SMP PREEMPT_DYNAMIC Fri Oct 31 13:55:05 UTC 2025 x86_64 x86_64 x86_64 GNU/Linux Sun Mar 1 13:43:00 EST 2026 tmpdir is ./tmp.mri_nu_correct.mni.3364139 cd /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri AntsN4BiasFieldCorrectionFs -i orig.mgz -o ./tmp.mri_nu_correct.mni.3364139/nu0.mgz --dtype uchar AntsN4BiasFieldCorrectionFs done mri_convert ./tmp.mri_nu_correct.mni.3364139/nu0.mgz orig_nu.mgz --like orig.mgz --conform mri_convert ./tmp.mri_nu_correct.mni.3364139/nu0.mgz orig_nu.mgz --like orig.mgz --conform reading from ./tmp.mri_nu_correct.mni.3364139/nu0.mgz... TR=1900.00, TE=0.00, TI=0.00, flip angle=0.00 i_ras = (-1, 0, 0) j_ras = (0, 0, -1) k_ras = (0, 1, 0) INFO: transform src into the like-volume: orig.mgz writing to orig_nu.mgz... Sun Mar 1 13:46:08 EST 2026 mri_nu_correct.mni done @#@FSTIME 2026:03:01:13:43:00 mri_nu_correct.mni N 12 e 188.16 S 0.21 U 187.36 P 99% M 506664 F 0 R 25738 W 0 c 98 w 148 I 0 O 0 L 0.70 0.25 0.19 @#@FSLOADPOST 2026:03:01:13:46:08 mri_nu_correct.mni N 12 1.03 0.63 0.35 talairach_avi --i orig_nu.mgz --xfm transforms/talairach.auto.xfm talairach_avi log file is transforms/talairach_avi.log... Started at Sun Mar 1 13:46:08 EST 2026 Ended at Sun Mar 1 13:46:28 EST 2026 talairach_avi done @#@FSTIME 2026:03:01:13:46:08 talairach_avi N 4 e 19.70 S 0.77 U 12.82 P 69% M 255108 F 0 R 30446 W 0 c 43 w 313 I 0 O 32 L 1.03 0.63 0.35 @#@FSLOADPOST 2026:03:01:13:46:28 talairach_avi N 4 0.95 0.64 0.36 cp transforms/talairach.auto.xfm transforms/talairach.xfm lta_convert --src orig.mgz --trg /hpc/packages/minerva-centos7/freesurfer/7.2.0/freesurfer/average/mni305.cor.mgz --inxfm transforms/talairach.xfm --outlta transforms/talairach.xfm.lta --subject fsaverage --ltavox2vox 7.2.0 --src: orig.mgz src image (geometry). --trg: /hpc/packages/minerva-centos7/freesurfer/7.2.0/freesurfer/average/mni305.cor.mgz trg image (geometry). --inmni: transforms/talairach.xfm input MNI/XFM transform. --outlta: transforms/talairach.xfm.lta output LTA. --s: fsaverage subject name --ltavox2vox: output LTA as VOX_TO_VOX transform. LTA read, type : 1 1.02296 -0.01771 0.04970 -4.19279; -0.01493 0.93922 0.39779 -31.88879; -0.04437 -0.37613 1.03401 5.25003; 0.00000 0.00000 0.00000 1.00000; setting subject to fsaverage Writing LTA to file transforms/talairach.xfm.lta... lta_convert successful. #-------------------------------------------- #@# Talairach Failure Detection Sun Mar 1 13:46:30 EST 2026 /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri talairach_afd -T 0.005 -xfm transforms/talairach.xfm talairach_afd: Talairach Transform: transforms/talairach.xfm OK (p=0.5655, pval=0.2115 >= threshold=0.0050) @#@FSTIME 2026:03:01:13:46:30 talairach_afd N 4 e 0.00 S 0.00 U 0.00 P 71% M 4608 F 0 R 228 W 0 c 2 w 7 I 0 O 0 L 0.87 0.63 0.36 @#@FSLOADPOST 2026:03:01:13:46:30 talairach_afd N 4 0.87 0.63 0.36 awk -f /hpc/packages/minerva-centos7/freesurfer/7.2.0/freesurfer/bin/extract_talairach_avi_QA.awk /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/transforms/talairach_avi.log tal_QC_AZS /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/transforms/talairach_avi.log TalAviQA: 0.97436 z-score: 0 #-------------------------------------------- #@# Nu Intensity Correction Sun Mar 1 13:46:30 EST 2026 mri_nu_correct.mni --i orig.mgz --o nu.mgz --uchar transforms/talairach.xfm --n 2 --ants-n4 /usr/bin/bc /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri /hpc/packages/minerva-centos7/freesurfer/7.2.0/freesurfer/bin/mri_nu_correct.mni --i orig.mgz --o nu.mgz --uchar transforms/talairach.xfm --n 2 --ants-n4 nIters 2 mri_nu_correct.mni 7.2.0 Linux lh06c22 5.14.0-570.58.1.el9_6.x86_64 #1 SMP PREEMPT_DYNAMIC Fri Oct 31 13:55:05 UTC 2025 x86_64 x86_64 x86_64 GNU/Linux Sun Mar 1 13:46:30 EST 2026 tmpdir is ./tmp.mri_nu_correct.mni.3365465 cd /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri AntsN4BiasFieldCorrectionFs -i orig.mgz -o ./tmp.mri_nu_correct.mni.3365465/nu0.mgz --dtype uchar AntsN4BiasFieldCorrectionFs done mri_binarize --i ./tmp.mri_nu_correct.mni.3365465/nu0.mgz --min -1 --o ./tmp.mri_nu_correct.mni.3365465/ones.mgz 7.2.0 cwd /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri cmdline mri_binarize --i ./tmp.mri_nu_correct.mni.3365465/nu0.mgz --min -1 --o ./tmp.mri_nu_correct.mni.3365465/ones.mgz sysname Linux hostname lh06c22 machine x86_64 user walesr01 input ./tmp.mri_nu_correct.mni.3365465/nu0.mgz frame 0 nErode3d 0 nErode2d 0 output ./tmp.mri_nu_correct.mni.3365465/ones.mgz Binarizing based on threshold min -1 max +infinity binval 1 binvalnot 0 fstart = 0, fend = 0, nframes = 1 Starting parallel 1 Found 16777216 values in range Counting number of voxels in first frame Found 16777215 voxels in final mask Writing output to ./tmp.mri_nu_correct.mni.3365465/ones.mgz Count: 16777215 16777215.000000 16777216 99.999994 mri_binarize done mri_segstats --id 1 --seg ./tmp.mri_nu_correct.mni.3365465/ones.mgz --i orig.mgz --sum ./tmp.mri_nu_correct.mni.3365465/sum.junk --avgwf ./tmp.mri_nu_correct.mni.3365465/input.mean.dat 7.2.0 cwd cmdline mri_segstats --id 1 --seg ./tmp.mri_nu_correct.mni.3365465/ones.mgz --i orig.mgz --sum ./tmp.mri_nu_correct.mni.3365465/sum.junk --avgwf ./tmp.mri_nu_correct.mni.3365465/input.mean.dat sysname Linux hostname lh06c22 machine x86_64 user walesr01 whitesurfname white UseRobust 0 Loading ./tmp.mri_nu_correct.mni.3365465/ones.mgz Loading orig.mgz Voxel Volume is 1 mm^3 Generating list of segmentation ids Found 1 segmentations Computing statistics for each segmentation Reporting on 1 segmentations Using PrintSegStat Computing spatial average of each frame 0 Writing to ./tmp.mri_nu_correct.mni.3365465/input.mean.dat mri_segstats done mri_segstats --id 1 --seg ./tmp.mri_nu_correct.mni.3365465/ones.mgz --i ./tmp.mri_nu_correct.mni.3365465/nu0.mgz --sum ./tmp.mri_nu_correct.mni.3365465/sum.junk --avgwf ./tmp.mri_nu_correct.mni.3365465/output.mean.dat 7.2.0 cwd cmdline mri_segstats --id 1 --seg ./tmp.mri_nu_correct.mni.3365465/ones.mgz --i ./tmp.mri_nu_correct.mni.3365465/nu0.mgz --sum ./tmp.mri_nu_correct.mni.3365465/sum.junk --avgwf ./tmp.mri_nu_correct.mni.3365465/output.mean.dat sysname Linux hostname lh06c22 machine x86_64 user walesr01 whitesurfname white UseRobust 0 Loading ./tmp.mri_nu_correct.mni.3365465/ones.mgz Loading ./tmp.mri_nu_correct.mni.3365465/nu0.mgz Voxel Volume is 1 mm^3 Generating list of segmentation ids Found 1 segmentations Computing statistics for each segmentation Reporting on 1 segmentations Using PrintSegStat Computing spatial average of each frame 0 Writing to ./tmp.mri_nu_correct.mni.3365465/output.mean.dat mri_segstats done mris_calc -o ./tmp.mri_nu_correct.mni.3365465/nu0.mgz ./tmp.mri_nu_correct.mni.3365465/nu0.mgz mul 1.22647957831568829138 Saving result to './tmp.mri_nu_correct.mni.3365465/nu0.mgz' (type = MGH ) [ ok ] mri_convert ./tmp.mri_nu_correct.mni.3365465/nu0.mgz nu.mgz --like orig.mgz mri_convert ./tmp.mri_nu_correct.mni.3365465/nu0.mgz nu.mgz --like orig.mgz reading from ./tmp.mri_nu_correct.mni.3365465/nu0.mgz... TR=1900.00, TE=0.00, TI=0.00, flip angle=0.00 i_ras = (-1, 0, 0) j_ras = (0, 0, -1) k_ras = (0, 1, 0) INFO: transform src into the like-volume: orig.mgz writing to nu.mgz... mri_make_uchar nu.mgz transforms/talairach.xfm nu.mgz type change took 0 minutes and 5 seconds. mapping ( 8, 103) to ( 3, 110) Sun Mar 1 13:49:59 EST 2026 mri_nu_correct.mni done @#@FSTIME 2026:03:01:13:46:30 mri_nu_correct.mni N 9 e 208.41 S 0.67 U 207.01 P 99% M 613032 F 0 R 174286 W 0 c 185 w 271 I 0 O 0 L 0.87 0.63 0.36 @#@FSLOADPOST 2026:03:01:13:49:59 mri_nu_correct.mni N 9 1.03 0.85 0.51 mri_add_xform_to_header -c /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/transforms/talairach.xfm nu.mgz nu.mgz INFO: extension is mgz @#@FSTIME 2026:03:01:13:49:59 mri_add_xform_to_header N 4 e 0.45 S 0.00 U 0.44 P 99% M 22744 F 0 R 998 W 0 c 2 w 8 I 0 O 0 L 1.03 0.85 0.51 @#@FSLOADPOST 2026:03:01:13:49:59 mri_add_xform_to_header N 4 1.03 0.85 0.51 #-------------------------------------------- #@# Intensity Normalization Sun Mar 1 13:49:59 EST 2026 /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri mri_normalize -g 1 -seed 1234 -mprage -W ctrl_vol.mgz bias_vol.mgz nu.mgz T1.mgz using max gradient = 1.000 setting seed for random number genererator to 1234 assuming input volume is MGH (Van der Kouwe) MP-RAGE writing ctrl pts to ctrl_vol.mgz writing bias field to bias_vol.mgz reading mri_src from nu.mgz... normalizing image... NOT doing gentle normalization with control points/label talairach transform 1.02296 -0.01771 0.04970 -4.19279; -0.01493 0.93922 0.39779 -31.88879; -0.04437 -0.37613 1.03401 5.25003; 0.00000 0.00000 0.00000 1.00000; processing without aseg, no1d=0 MRInormInit(): INFO: Modifying talairach volume c_(r,a,s) based on average_305 MRInormalize(): MRIsplineNormalize(): npeaks = 18 Starting OpenSpline(): npoints = 18 writing control point volume to ctrl_vol.mgz... writing control point volume to ctrl_vol.mgz... writing control point volume to ctrl_vol.mgz... building Voronoi diagram... performing soap bubble smoothing, sigma = 8... Iterating 2 times --------------------------------- 3d normalization pass 1 of 2 white matter peak found at 110 white matter peak found at 109 gm peak at 81 (81), valley at 47 (47) csf peak at 28, setting threshold to 63 building Voronoi diagram... performing soap bubble smoothing, sigma = 8... --------------------------------- 3d normalization pass 2 of 2 white matter peak found at 110 white matter peak found at 110 gm peak at 80 (80), valley at 45 (45) csf peak at 29, setting threshold to 63 building Voronoi diagram... performing soap bubble smoothing, sigma = 8... Done iterating --------------------------------- writing bias field to bias_vol.mgz.... writing output to T1.mgz 3D bias adjustment took 1 minutes and 35 seconds. @#@FSTIME 2026:03:01:13:49:59 mri_normalize N 10 e 95.15 S 0.23 U 94.57 P 99% M 582948 F 0 R 14196 W 0 c 91 w 31 I 0 O 0 L 1.03 0.85 0.51 @#@FSLOADPOST 2026:03:01:13:51:34 mri_normalize N 10 1.02 0.91 0.57 #-------------------------------------------- #@# Skull Stripping Sun Mar 1 13:51:34 EST 2026 /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri mri_mask -keep_mask_deletion_edits T1.mgz brainmask_template.mgz brainmask.auto.mgz Transferring mask edits ('1' voxels) to dst vol DoAbs = 0 Writing masked volume to brainmask.auto.mgz...done. @#@FSTIME 2026:03:01:13:51:34 mri_mask N 4 e 0.93 S 0.03 U 0.89 P 99% M 89268 F 0 R 3533 W 0 c 5 w 13 I 0 O 0 L 1.02 0.91 0.57 @#@FSLOADPOST 2026:03:01:13:51:35 mri_mask N 4 1.02 0.91 0.57 mri_mask -transfer 255 -keep_mask_deletion_edits brainmask.auto.mgz brainmask_template.mgz brainmask.auto.mgz transfer mask voxels=255 to dst vol Transferring mask edits ('1' voxels) to dst vol DoAbs = 0 Writing masked volume to brainmask.auto.mgz...done. @#@FSTIME 2026:03:01:13:51:35 mri_mask N 6 e 0.98 S 0.02 U 0.95 P 99% M 90212 F 0 R 3536 W 0 c 3 w 9 I 0 O 0 L 1.02 0.91 0.57 @#@FSLOADPOST 2026:03:01:13:51:36 mri_mask N 6 1.02 0.91 0.57 cp brainmask.auto.mgz brainmask.mgz #------------------------------------- #@# EM Registration Sun Mar 1 13:51:37 EST 2026 /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri mri_em_register -mask brainmask.mgz norm_template.mgz /hpc/packages/minerva-centos7/freesurfer/7.2.0/freesurfer/average/RB_all_2020-01-02.gca transforms/talairach.lta using MR volume brainmask.mgz to mask input volume... == Number of threads available to mri_em_register for OpenMP = 1 == reading 1 input volumes... logging results to talairach.log reading '/hpc/packages/minerva-centos7/freesurfer/7.2.0/freesurfer/average/RB_all_2020-01-02.gca'... GCAread took 0 minutes and 1 seconds. average std = 7.2 using min determinant for regularization = 5.2 0 singular and 884 ill-conditioned covariance matrices regularized reading 'norm_template.mgz'... MRImask(): AllowDiffGeom = 1 MRImask(): AllowDiffGeom = 1 MRImask(): AllowDiffGeom = 1 MRImask(): AllowDiffGeom = 1 MRImask(): AllowDiffGeom = 1 freeing gibbs priors...done. accounting for voxel sizes in initial transform bounding unknown intensity as < 5.9 or > 519.0 total sample mean = 78.8 (495 zeros) ************************************************ spacing=8, using 2251 sample points, tol=1.00e-05... ************************************************ register_mri: find_optimal_transform find_optimal_transform: nsamples 2251, passno 0, spacing 8 resetting wm mean[0]: 98 --> 107 resetting gm mean[0]: 61 --> 61 input volume #1 is the most T1-like using real data threshold=20.0 skull bounding box = (58, 67, 51) --> (197, 207, 219) finding center of left hemi white matter using (104, 114, 135) as brain centroid of Right_Cerebral_White_Matter... MRImask(): AllowDiffGeom = 1 mean wm in atlas = 107, using box (87,97,114) --> (121, 131,155) to find MRI wm before smoothing, mri peak at 102 robust fit to distribution - 102 +- 4.9 after smoothing, mri peak at 102, scaling input intensities by 1.049 scaling channel 0 by 1.04902 initial log_p = -4.772 ************************************************ First Search limited to translation only. ************************************************ max log p = -4.432881 @ (-10.526, -10.526, -31.579) max log p = -4.193294 @ (5.263, 5.263, 5.263) max log p = -4.082139 @ (2.632, -2.632, -2.632) max log p = -4.019383 @ (1.316, 1.316, 3.947) max log p = -4.019383 @ (0.000, 0.000, 0.000) max log p = -4.015929 @ (0.987, -0.329, -2.303) max log p = -4.015929 @ (0.000, 0.000, 0.000) max log p = -4.015929 @ (0.000, 0.000, 0.000) Found translation: (-0.3, -6.9, -27.3): log p = -4.016 **************************************** Nine parameter search. iteration 0 nscales = 0 ... **************************************** Result so far: scale 1.000: max_log_p=-3.738, old_max_log_p =-4.016 (thresh=-4.0) 1.00000 0.00000 0.00000 -0.32895; 0.00000 0.99317 0.41138 -60.64647; 0.00000 -0.38268 0.92388 38.59428; 0.00000 0.00000 0.00000 1.00000; iteration took 0 minutes and 54 seconds. **************************************** Nine parameter search. iteration 1 nscales = 0 ... **************************************** Result so far: scale 1.000: max_log_p=-3.728, old_max_log_p =-3.738 (thresh=-3.7) 1.00000 0.00000 0.00000 -0.32895; 0.00000 1.06766 0.44224 -74.14174; 0.00000 -0.35398 0.85459 43.60627; 0.00000 0.00000 0.00000 1.00000; iteration took 0 minutes and 54 seconds. **************************************** Nine parameter search. iteration 2 nscales = 0 ... **************************************** Result so far: scale 1.000: max_log_p=-3.728, old_max_log_p =-3.728 (thresh=-3.7) 1.00000 0.00000 0.00000 -0.32895; 0.00000 1.06766 0.44224 -74.14174; 0.00000 -0.35398 0.85459 43.60627; 0.00000 0.00000 0.00000 1.00000; reducing scale to 0.2500 iteration took 0 minutes and 54 seconds. **************************************** Nine parameter search. iteration 3 nscales = 1 ... **************************************** Result so far: scale 0.250: max_log_p=-3.554, old_max_log_p =-3.728 (thresh=-3.7) 0.97869 0.07919 -0.00053 -9.65298; -0.06292 1.03689 0.39551 -54.41991; 0.03116 -0.33725 0.91741 27.83281; 0.00000 0.00000 0.00000 1.00000; iteration took 0 minutes and 53 seconds. **************************************** Nine parameter search. iteration 4 nscales = 1 ... **************************************** Result so far: scale 0.250: max_log_p=-3.554, old_max_log_p =-3.554 (thresh=-3.6) 0.97869 0.07919 -0.00053 -9.65298; -0.06292 1.03689 0.39551 -54.41991; 0.03116 -0.33725 0.91741 27.83281; 0.00000 0.00000 0.00000 1.00000; reducing scale to 0.0625 iteration took 0 minutes and 53 seconds. **************************************** Nine parameter search. iteration 5 nscales = 2 ... **************************************** Result so far: scale 0.062: max_log_p=-3.536, old_max_log_p =-3.554 (thresh=-3.6) 0.98023 0.07347 0.01439 -10.08023; -0.06247 1.03244 0.41094 -54.93255; 0.01619 -0.35584 0.91177 32.84310; 0.00000 0.00000 0.00000 1.00000; iteration took 0 minutes and 51 seconds. **************************************** Nine parameter search. iteration 6 nscales = 2 ... **************************************** Result so far: scale 0.062: max_log_p=-3.535, old_max_log_p =-3.536 (thresh=-3.5) 0.97909 0.07338 0.01437 -9.91982; -0.06241 1.03070 0.41888 -56.19409; 0.01670 -0.36427 0.90837 34.73961; 0.00000 0.00000 0.00000 1.00000; min search scale 0.025000 reached *********************************************** Computing MAP estimate using 2251 samples... *********************************************** dt = 5.00e-06, momentum=0.80, tol=1.00e-05 l_intensity = 1.0000 Aligning input volume to GCA... Transform matrix 0.97909 0.07338 0.01437 -9.91982; -0.06241 1.03070 0.41888 -56.19409; 0.01670 -0.36427 0.90837 34.73961; 0.00000 0.00000 0.00000 1.00000; nsamples 2251 Quasinewton: input matrix 0.97909 0.07338 0.01437 -9.91982; -0.06241 1.03070 0.41888 -56.19409; 0.01670 -0.36427 0.90837 34.73961; 0.00000 0.00000 0.00000 1.00000; IFLAG= -1 LINE SEARCH FAILED. SEE DOCUMENTATION OF ROUTINE MCSRCH ERROR RETURN OF LINE SEARCH: INFO= 4 POSSIBLE CAUSES: FUNCTION OR GRADIENT ARE INCORRECT OR INCORRECT TOLERANCESoutof QuasiNewtonEMA: 009: -log(p) = -0.0 tol 0.000010 Resulting transform: 0.97909 0.07338 0.01437 -9.91982; -0.06241 1.03070 0.41888 -56.19409; 0.01670 -0.36427 0.90837 34.73961; 0.00000 0.00000 0.00000 1.00000; pass 1, spacing 8: log(p) = -3.535 (old=-4.772) transform before final EM align: 0.97909 0.07338 0.01437 -9.91982; -0.06241 1.03070 0.41888 -56.19409; 0.01670 -0.36427 0.90837 34.73961; 0.00000 0.00000 0.00000 1.00000; ************************************************** EM alignment process ... Computing final MAP estimate using 246437 samples. ************************************************** dt = 5.00e-06, momentum=0.80, tol=1.00e-07 l_intensity = 1.0000 Aligning input volume to GCA... Transform matrix 0.97909 0.07338 0.01437 -9.91982; -0.06241 1.03070 0.41888 -56.19409; 0.01670 -0.36427 0.90837 34.73961; 0.00000 0.00000 0.00000 1.00000; nsamples 246437 Quasinewton: input matrix 0.97909 0.07338 0.01437 -9.91982; -0.06241 1.03070 0.41888 -56.19409; 0.01670 -0.36427 0.90837 34.73961; 0.00000 0.00000 0.00000 1.00000; IFLAG= -1 LINE SEARCH FAILED. SEE DOCUMENTATION OF ROUTINE MCSRCH ERROR RETURN OF LINE SEARCH: INFO= 6 POSSIBLE CAUSES: FUNCTION OR GRADIENT ARE INCORRECT OR INCORRECT TOLERANCESoutof QuasiNewtonEMA: 011: -log(p) = 4.2 tol 0.000000 final transform: 0.97909 0.07338 0.01437 -9.91982; -0.06241 1.03070 0.41888 -56.19409; 0.01670 -0.36427 0.90837 34.73961; 0.00000 0.00000 0.00000 1.00000; writing output transformation to transforms/talairach.lta... #VMPC# mri_em_register VmPeak 767164 FSRUNTIME@ mri_em_register 0.1130 hours 1 threads registration took 6 minutes and 47 seconds. @#@FSTIME 2026:03:01:13:51:37 mri_em_register N 5 e 406.88 S 0.81 U 404.46 P 99% M 615760 F 0 R 114273 W 0 c 233 w 12 I 0 O 0 L 1.02 0.91 0.57 @#@FSLOADPOST 2026:03:01:13:58:24 mri_em_register N 5 1.06 1.01 0.75 #-------------------------------------- #@# CA Normalize Sun Mar 1 13:58:24 EST 2026 /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri mri_ca_normalize -c ctrl_pts.mgz -mask brainmask.mgz norm_template.mgz /hpc/packages/minerva-centos7/freesurfer/7.2.0/freesurfer/average/RB_all_2020-01-02.gca transforms/talairach.lta norm.mgz writing control point volume to ctrl_pts.mgz using MR volume brainmask.mgz to mask input volume... reading 1 input volume reading atlas from '/hpc/packages/minerva-centos7/freesurfer/7.2.0/freesurfer/average/RB_all_2020-01-02.gca'... reading transform from 'transforms/talairach.lta'... reading input volume from norm_template.mgz... resetting wm mean[0]: 98 --> 107 resetting gm mean[0]: 61 --> 61 input volume #1 is the most T1-like using real data threshold=20.0 skull bounding box = (58, 67, 51) --> (197, 207, 219) finding center of left hemi white matter using (104, 114, 135) as brain centroid of Right_Cerebral_White_Matter... mean wm in atlas = 107, using box (87,97,114) --> (121, 131,155) to find MRI wm before smoothing, mri peak at 102 robust fit to distribution - 102 +- 4.9 after smoothing, mri peak at 102, scaling input intensities by 1.049 scaling channel 0 by 1.04902 using 246437 sample points... INFO: compute sample coordinates transform 0.97909 0.07338 0.01437 -9.91982; -0.06241 1.03070 0.41888 -56.19409; 0.01670 -0.36427 0.90837 34.73961; 0.00000 0.00000 0.00000 1.00000; INFO: transform used finding control points in Left_Cerebral_White_Matter.... found 40230 control points for structure... bounding box (125, 66, 52) --> (196, 183, 216) Left_Cerebral_White_Matter: limiting intensities to 96.0 --> 132.0 2 of 1623 (0.1%) samples deleted finding control points in Right_Cerebral_White_Matter.... found 39478 control points for structure... bounding box (61, 64, 51) --> (131, 172, 216) Right_Cerebral_White_Matter: limiting intensities to 93.0 --> 132.0 3 of 2197 (0.1%) samples deleted finding control points in Left_Cerebellum_White_Matter.... found 3105 control points for structure... bounding box (126, 150, 86) --> (175, 195, 139) Left_Cerebellum_White_Matter: limiting intensities to 88.0 --> 132.0 10 of 94 (10.6%) samples deleted finding control points in Right_Cerebellum_White_Matter.... found 2710 control points for structure... bounding box (79, 150, 82) --> (126, 191, 139) Right_Cerebellum_White_Matter: limiting intensities to 88.0 --> 132.0 19 of 117 (16.2%) samples deleted finding control points in Brain_Stem.... found 3475 control points for structure... bounding box (108, 137, 118) --> (144, 199, 149) Brain_Stem: limiting intensities to 88.0 --> 132.0 69 of 247 (27.9%) samples deleted using 4278 total control points for intensity normalization... bias field = 0.959 +- 0.039 25 of 4175 control points discarded finding control points in Left_Cerebral_White_Matter.... found 40230 control points for structure... bounding box (125, 66, 52) --> (196, 183, 216) Left_Cerebral_White_Matter: limiting intensities to 91.0 --> 132.0 2 of 2139 (0.1%) samples deleted finding control points in Right_Cerebral_White_Matter.... found 39478 control points for structure... bounding box (61, 64, 51) --> (131, 172, 216) Right_Cerebral_White_Matter: limiting intensities to 88.0 --> 132.0 6 of 2776 (0.2%) samples deleted finding control points in Left_Cerebellum_White_Matter.... found 3105 control points for structure... bounding box (126, 150, 86) --> (175, 195, 139) Left_Cerebellum_White_Matter: limiting intensities to 88.0 --> 132.0 72 of 114 (63.2%) samples deleted finding control points in Right_Cerebellum_White_Matter.... found 2710 control points for structure... bounding box (79, 150, 82) --> (126, 191, 139) Right_Cerebellum_White_Matter: limiting intensities to 88.0 --> 132.0 122 of 155 (78.7%) samples deleted finding control points in Brain_Stem.... found 3475 control points for structure... bounding box (108, 137, 118) --> (144, 199, 149) Brain_Stem: limiting intensities to 88.0 --> 132.0 227 of 312 (72.8%) samples deleted using 5496 total control points for intensity normalization... bias field = 1.009 +- 0.039 22 of 5025 control points discarded finding control points in Left_Cerebral_White_Matter.... found 40230 control points for structure... bounding box (125, 66, 52) --> (196, 183, 216) Left_Cerebral_White_Matter: limiting intensities to 90.0 --> 132.0 2 of 2168 (0.1%) samples deleted finding control points in Right_Cerebral_White_Matter.... found 39478 control points for structure... bounding box (61, 64, 51) --> (131, 172, 216) Right_Cerebral_White_Matter: limiting intensities to 88.0 --> 132.0 7 of 2738 (0.3%) samples deleted finding control points in Left_Cerebellum_White_Matter.... found 3105 control points for structure... bounding box (126, 150, 86) --> (175, 195, 139) Left_Cerebellum_White_Matter: limiting intensities to 88.0 --> 132.0 154 of 190 (81.1%) samples deleted finding control points in Right_Cerebellum_White_Matter.... found 2710 control points for structure... bounding box (79, 150, 82) --> (126, 191, 139) Right_Cerebellum_White_Matter: limiting intensities to 88.0 --> 132.0 185 of 207 (89.4%) samples deleted finding control points in Brain_Stem.... found 3475 control points for structure... bounding box (108, 137, 118) --> (144, 199, 149) Brain_Stem: limiting intensities to 88.0 --> 132.0 297 of 376 (79.0%) samples deleted using 5679 total control points for intensity normalization... bias field = 1.009 +- 0.037 22 of 4949 control points discarded writing normalized volume to norm.mgz... writing control points to ctrl_pts.mgz freeing GCA...done. normalization took 1 minutes and 3 seconds. @#@FSTIME 2026:03:01:13:58:24 mri_ca_normalize N 8 e 62.54 S 0.45 U 61.86 P 99% M 904236 F 0 R 136903 W 0 c 74 w 19 I 0 O 0 L 1.37 1.07 0.77 @#@FSLOADPOST 2026:03:01:13:59:27 mri_ca_normalize N 8 1.13 1.06 0.79 #-------------------------------------- #@# CA Reg Sun Mar 1 13:59:27 EST 2026 /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri mri_ca_register -nobigventricles -T transforms/talairach.lta -align-after -mask brainmask.mgz norm.mgz /hpc/packages/minerva-centos7/freesurfer/7.2.0/freesurfer/average/RB_all_2020-01-02.gca transforms/talairach.m3z not handling expanded ventricles... using previously computed transform transforms/talairach.lta renormalizing sequences with structure alignment, equivalent to: -renormalize -regularize_mean 0.500 -regularize 0.500 using MR volume brainmask.mgz to mask input volume... == Number of threads available to mri_ca_register for OpenMP = 1 == reading 1 input volumes... logging results to talairach.log reading input volume 'norm.mgz'... reading GCA '/hpc/packages/minerva-centos7/freesurfer/7.2.0/freesurfer/average/RB_all_2020-01-02.gca'... label assignment complete, 0 changed (0.00%) freeing gibbs priors...done. average std[0] = 5.0 Starting GCAMregister() label assignment complete, 0 changed (0.00%) npasses = 1, nlevels = 6 #pass# 1 of 1 ************************ enabling zero nodes setting smoothness cost coefficient to 0.156 #GCAMreg# pass 0 level1 5 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.16 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=256, sigma=2.0,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.843038 #FOTS# QuadFit found better minimum quadopt=(dt=208.405,rms=0.788078) vs oldopt=(dt=92.48,rms=0.805522) #GCMRL# 0 dt 208.405365 rms 0.788 6.519% neg 0 invalid 762 tFOTS 15.6400 tGradient 6.5280 tsec 23.3160 #FOTS# QuadFit found better minimum quadopt=(dt=295.936,rms=0.772596) vs oldopt=(dt=369.92,rms=0.773629) #GCMRL# 1 dt 295.936000 rms 0.773 1.964% neg 0 invalid 762 tFOTS 15.6270 tGradient 6.8920 tsec 23.6700 #FOTS# QuadFit found better minimum quadopt=(dt=206,rms=0.763958) vs oldopt=(dt=92.48,rms=0.767041) #GCMRL# 2 dt 206.000000 rms 0.764 1.118% neg 0 invalid 762 tFOTS 15.6080 tGradient 6.6010 tsec 23.3570 #FOTS# QuadFit found better minimum quadopt=(dt=295.936,rms=0.759495) vs oldopt=(dt=369.92,rms=0.759767) #GCMRL# 3 dt 295.936000 rms 0.759 0.584% neg 0 invalid 762 tFOTS 14.6930 tGradient 6.7350 tsec 22.5760 #FOTS# QuadFit found better minimum quadopt=(dt=295.936,rms=0.754436) vs oldopt=(dt=369.92,rms=0.755082) #GCMRL# 4 dt 295.936000 rms 0.754 0.666% neg 0 invalid 762 tFOTS 15.6200 tGradient 6.6020 tsec 23.3720 #FOTS# QuadFit found better minimum quadopt=(dt=129.472,rms=0.752112) vs oldopt=(dt=92.48,rms=0.752453) #GCMRL# 5 dt 129.472000 rms 0.752 0.308% neg 0 invalid 762 tFOTS 14.6790 tGradient 6.6560 tsec 22.4860 #FOTS# QuadFit found better minimum quadopt=(dt=2071.55,rms=0.735684) vs oldopt=(dt=1479.68,rms=0.738941) #GCMRL# 6 dt 2071.552000 rms 0.736 2.184% neg 0 invalid 762 tFOTS 15.6200 tGradient 6.8180 tsec 23.5890 #FOTS# QuadFit found better minimum quadopt=(dt=129.472,rms=0.7349) vs oldopt=(dt=92.48,rms=0.735017) #GCMRL# 7 dt 129.472000 rms 0.735 0.000% neg 0 invalid 762 tFOTS 15.6050 tGradient 6.6250 tsec 23.4150 #GCMRL# 8 dt 129.472000 rms 0.734 0.056% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6910 tsec 7.8410 #GCMRL# 9 dt 129.472000 rms 0.734 0.084% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6900 tsec 7.8610 #GCMRL# 10 dt 129.472000 rms 0.733 0.113% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6480 tsec 7.7990 #GCMRL# 11 dt 129.472000 rms 0.732 0.164% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.7920 tsec 7.9410 #GCMRL# 12 dt 129.472000 rms 0.730 0.184% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.7200 tsec 7.8700 #GCMRL# 13 dt 129.472000 rms 0.729 0.202% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.7290 tsec 7.8790 #GCMRL# 14 dt 129.472000 rms 0.727 0.235% neg 0 invalid 762 tFOTS 0.0000 tGradient 7.4590 tsec 8.6090 #GCMRL# 15 dt 129.472000 rms 0.725 0.258% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6800 tsec 7.8310 #GCMRL# 16 dt 129.472000 rms 0.723 0.308% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.7380 tsec 7.8880 #GCMRL# 17 dt 129.472000 rms 0.721 0.310% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.8010 tsec 7.9520 #GCMRL# 18 dt 129.472000 rms 0.719 0.303% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.7770 tsec 7.9260 #GCMRL# 19 dt 129.472000 rms 0.717 0.291% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.7450 tsec 7.8940 #GCMRL# 20 dt 129.472000 rms 0.715 0.246% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6400 tsec 7.7920 #GCMRL# 21 dt 129.472000 rms 0.713 0.212% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6240 tsec 7.7740 #GCMRL# 22 dt 129.472000 rms 0.712 0.213% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6410 tsec 7.7910 #GCMRL# 23 dt 129.472000 rms 0.710 0.199% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.9210 tsec 8.0730 #GCMRL# 24 dt 129.472000 rms 0.709 0.169% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.7570 tsec 7.9130 #GCMRL# 25 dt 129.472000 rms 0.708 0.154% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6590 tsec 7.8140 #GCMRL# 26 dt 129.472000 rms 0.707 0.132% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6100 tsec 7.7610 #GCMRL# 27 dt 129.472000 rms 0.706 0.138% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.7260 tsec 7.8780 #GCMRL# 28 dt 129.472000 rms 0.705 0.139% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6480 tsec 7.7980 #GCMRL# 29 dt 129.472000 rms 0.704 0.123% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6580 tsec 7.8080 #GCMRL# 30 dt 129.472000 rms 0.704 0.094% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6190 tsec 7.8080 #FOTS# QuadFit found better minimum quadopt=(dt=1775.62,rms=0.703204) vs oldopt=(dt=1479.68,rms=0.703214) #GCMRL# 31 dt 1775.616000 rms 0.703 0.000% neg 0 invalid 762 tFOTS 16.5160 tGradient 6.6080 tsec 24.3110 #GCAMreg# pass 0 level1 5 level2 1 tsec 404.936 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.16 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=256, sigma=0.5,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.703763 #FOTS# QuadFit found better minimum quadopt=(dt=129.472,rms=0.70294) vs oldopt=(dt=92.48,rms=0.702989) #GCMRL# 33 dt 129.472000 rms 0.703 0.117% neg 0 invalid 762 tFOTS 15.6170 tGradient 6.5520 tsec 23.3170 #FOTS# QuadFit found better minimum quadopt=(dt=295.936,rms=0.702676) vs oldopt=(dt=369.92,rms=0.70269) #GCMRL# 34 dt 295.936000 rms 0.703 0.000% neg 0 invalid 762 tFOTS 15.6340 tGradient 6.7330 tsec 23.5540 #GCMRL# 35 dt 295.936000 rms 0.702 0.052% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6690 tsec 7.8220 #GCMRL# 36 dt 295.936000 rms 0.702 0.000% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6890 tsec 7.8380 setting smoothness cost coefficient to 0.615 #GCAMreg# pass 0 level1 4 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.62 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=64, sigma=2.0,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.71574 #FOTS# QuadFit found better minimum quadopt=(dt=36.288,rms=0.714365) vs oldopt=(dt=25.92,rms=0.714444) #GCMRL# 38 dt 36.288000 rms 0.714 0.192% neg 0 invalid 762 tFOTS 15.6170 tGradient 5.0810 tsec 21.8490 #FOTS# QuadFit found better minimum quadopt=(dt=36.288,rms=0.713754) vs oldopt=(dt=25.92,rms=0.71387) #GCMRL# 39 dt 36.288000 rms 0.714 0.000% neg 0 invalid 762 tFOTS 14.7070 tGradient 5.0390 tsec 20.9380 #GCMRL# 40 dt 36.288000 rms 0.713 0.092% neg 0 invalid 762 tFOTS 0.0000 tGradient 5.0100 tsec 6.1620 #GCMRL# 41 dt 36.288000 rms 0.712 0.110% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.9330 tsec 6.0840 #GCMRL# 42 dt 36.288000 rms 0.711 0.125% neg 0 invalid 762 tFOTS 0.0000 tGradient 5.0630 tsec 6.2130 #GCMRL# 43 dt 36.288000 rms 0.710 0.173% neg 0 invalid 762 tFOTS 0.0000 tGradient 5.1190 tsec 6.2710 #GCMRL# 44 dt 36.288000 rms 0.708 0.310% neg 0 invalid 762 tFOTS 0.0000 tGradient 5.0390 tsec 6.1940 #GCMRL# 45 dt 36.288000 rms 0.705 0.462% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.9650 tsec 6.1230 #GCMRL# 46 dt 36.288000 rms 0.701 0.566% neg 0 invalid 762 tFOTS 0.0000 tGradient 5.0090 tsec 6.1600 #GCMRL# 47 dt 36.288000 rms 0.697 0.598% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.9580 tsec 6.1090 #GCMRL# 48 dt 36.288000 rms 0.693 0.553% neg 0 invalid 762 tFOTS 0.0000 tGradient 5.0780 tsec 6.2290 #GCMRL# 49 dt 36.288000 rms 0.690 0.449% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.9370 tsec 6.0920 #GCMRL# 50 dt 36.288000 rms 0.687 0.304% neg 0 invalid 762 tFOTS 0.0000 tGradient 5.0050 tsec 6.1620 #GCMRL# 51 dt 36.288000 rms 0.686 0.153% neg 0 invalid 762 tFOTS 0.0000 tGradient 5.0120 tsec 6.1630 #GCMRL# 52 dt 36.288000 rms 0.686 0.020% neg 0 invalid 762 tFOTS 0.0000 tGradient 5.0020 tsec 6.1530 #GCMRL# 53 dt 36.288000 rms 0.686 -0.049% neg 0 invalid 762 tFOTS 0.0000 tGradient 5.1210 tsec 7.3510 #GCAMreg# pass 0 level1 4 level2 1 tsec 157.76 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.62 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=64, sigma=0.5,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.68694 #GCMRL# 55 dt 0.000000 rms 0.686 0.091% neg 0 invalid 762 tFOTS 14.7050 tGradient 5.1210 tsec 20.9730 setting smoothness cost coefficient to 2.353 #GCAMreg# pass 0 level1 3 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=2.35 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=16, sigma=2.0,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.720818 #GCMRL# 57 dt 2.000000 rms 0.720 0.121% neg 0 invalid 762 tFOTS 14.7000 tGradient 4.4490 tsec 20.2970 #GCMRL# 58 dt 0.000488 rms 0.720 0.000% neg 0 invalid 762 tFOTS 19.2530 tGradient 4.7430 tsec 25.1830 #GCAMreg# pass 0 level1 3 level2 1 tsec 56.99 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=2.35 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=16, sigma=0.5,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.72054 #FOTS# QuadFit found better minimum quadopt=(dt=0.175,rms=0.719927) vs oldopt=(dt=0.125,rms=0.719927) #GCMRL# 60 dt 0.175000 rms 0.720 0.085% neg 0 invalid 762 tFOTS 14.7080 tGradient 4.7470 tsec 20.6030 #FOTS# QuadFit found better minimum quadopt=(dt=0.04375,rms=0.719935) vs oldopt=(dt=0.03125,rms=0.719935) setting smoothness cost coefficient to 8.000 #GCAMreg# pass 0 level1 2 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=8.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=4, sigma=2.0,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.809785 #FOTS# QuadFit found better minimum quadopt=(dt=2.90332,rms=0.777925) vs oldopt=(dt=2.88,rms=0.777926) #GCMRL# 62 dt 2.903325 rms 0.778 3.934% neg 0 invalid 762 tFOTS 14.7090 tGradient 4.2050 tsec 20.0670 #FOTS# QuadFit found better minimum quadopt=(dt=1.96226,rms=0.77403) vs oldopt=(dt=2.88,rms=0.7749) #GCMRL# 63 dt 1.962264 rms 0.774 0.501% neg 0 invalid 762 tFOTS 14.6930 tGradient 3.6460 tsec 19.4890 #FOTS# QuadFit found better minimum quadopt=(dt=1.54167,rms=0.773335) vs oldopt=(dt=0.72,rms=0.773464) #GCMRL# 64 dt 1.541667 rms 0.773 0.000% neg 0 invalid 762 tFOTS 14.7030 tGradient 3.6660 tsec 19.5590 #GCAMreg# pass 0 level1 2 level2 1 tsec 69.69 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=8.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=4, sigma=0.5,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.773873 #GCMRL# 66 dt 0.000000 rms 0.773 0.070% neg 0 invalid 762 tFOTS 13.8030 tGradient 3.8020 tsec 18.7570 setting smoothness cost coefficient to 20.000 #GCAMreg# pass 0 level1 1 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=20.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=1, sigma=2.0,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.830567 #FOTS# QuadFit found better minimum quadopt=(dt=0.384,rms=0.828553) vs oldopt=(dt=0.32,rms=0.828605) #GCMRL# 68 dt 0.384000 rms 0.829 0.242% neg 0 invalid 762 tFOTS 14.6970 tGradient 3.6450 tsec 19.4930 #FOTS# QuadFit found better minimum quadopt=(dt=1.024,rms=0.821919) vs oldopt=(dt=1.28,rms=0.822308) #GCMRL# 69 dt 1.024000 rms 0.822 0.801% neg 0 invalid 762 tFOTS 14.7030 tGradient 3.5180 tsec 19.3730 #FOTS# QuadFit found better minimum quadopt=(dt=0.192,rms=0.82032) vs oldopt=(dt=0.32,rms=0.820668) #GCMRL# 70 dt 0.192000 rms 0.820 0.000% neg 0 invalid 762 tFOTS 14.7260 tGradient 3.5120 tsec 19.4240 #GCMRL# 71 dt 0.192000 rms 0.820 0.069% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.4670 tsec 4.6150 #GCMRL# 72 dt 0.192000 rms 0.819 0.067% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.4660 tsec 4.6190 #GCMRL# 73 dt 0.192000 rms 0.817 0.213% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.4920 tsec 4.6410 #GCMRL# 74 dt 0.192000 rms 0.815 0.332% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.5190 tsec 4.6730 #GCMRL# 75 dt 0.192000 rms 0.813 0.242% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.5980 tsec 4.7470 #GCMRL# 76 dt 0.192000 rms 0.812 0.101% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.4860 tsec 4.6360 #GCMRL# 77 dt 0.192000 rms 0.812 -0.021% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.4880 tsec 5.7160 #GCMRL# 78 dt 0.080000 rms 0.812 0.003% neg 0 invalid 762 tFOTS 14.6970 tGradient 3.4880 tsec 19.3360 #FOTS# QuadFit found better minimum quadopt=(dt=0.112,rms=0.811854) vs oldopt=(dt=0.08,rms=0.811867) #GCMRL# 79 dt 0.112000 rms 0.812 0.009% neg 0 invalid 762 tFOTS 14.6990 tGradient 3.6180 tsec 19.4660 #FOTS# QuadFit found better minimum quadopt=(dt=1.024,rms=0.811118) vs oldopt=(dt=1.28,rms=0.811127) #GCMRL# 80 dt 1.024000 rms 0.811 0.091% neg 0 invalid 762 tFOTS 14.6950 tGradient 3.5330 tsec 19.3760 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.809206) vs oldopt=(dt=0.32,rms=0.809526) #GCMRL# 81 dt 0.448000 rms 0.809 0.236% neg 0 invalid 762 tFOTS 14.6980 tGradient 3.4940 tsec 19.3460 #FOTS# QuadFit found better minimum quadopt=(dt=0.007,rms=0.80921) vs oldopt=(dt=0.005,rms=0.80921) #GCAMreg# pass 0 level1 1 level2 1 tsec 194.364 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=20.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=1, sigma=0.5,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.8097 #FOTS# QuadFit found better minimum quadopt=(dt=0.064,rms=0.809173) vs oldopt=(dt=0.08,rms=0.809175) #GCMRL# 83 dt 0.064000 rms 0.809 0.065% neg 0 invalid 762 tFOTS 14.7090 tGradient 3.4090 tsec 19.2660 #FOTS# QuadFit found better minimum quadopt=(dt=0.028,rms=0.80917) vs oldopt=(dt=0.02,rms=0.809171) #GCMRL# 84 dt 0.028000 rms 0.809 0.000% neg 0 invalid 762 tFOTS 14.7090 tGradient 3.5870 tsec 19.4820 #GCMRL# 85 dt 0.028000 rms 0.809 0.000% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.5870 tsec 4.7390 resetting metric properties... setting smoothness cost coefficient to 40.000 #GCAMreg# pass 0 level1 0 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=40.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=0, sigma=2.0,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.776054 #FOTS# QuadFit found better minimum quadopt=(dt=0.212081,rms=0.771042) vs oldopt=(dt=0.32,rms=0.771865) #GCMRL# 87 dt 0.212081 rms 0.771 0.646% neg 0 invalid 762 tFOTS 14.7040 tGradient 2.9170 tsec 18.7700 #FOTS# QuadFit found better minimum quadopt=(dt=0.024,rms=0.770813) vs oldopt=(dt=0.02,rms=0.770813) #GCMRL# 88 dt 0.024000 rms 0.771 0.000% neg 0 invalid 762 tFOTS 14.7220 tGradient 2.8140 tsec 18.7230 #GCAMreg# pass 0 level1 0 level2 1 tsec 47.109 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=40.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=0, sigma=0.5,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.771328 #FOTS# QuadFit found better minimum quadopt=(dt=0.007,rms=0.770785) vs oldopt=(dt=0.005,rms=0.770789) #GCMRL# 90 dt 0.007000 rms 0.771 0.071% neg 0 invalid 762 tFOTS 14.7140 tGradient 2.8350 tsec 18.6980 #FOTS# QuadFit found better minimum quadopt=(dt=0.003,rms=0.770778) vs oldopt=(dt=0.005,rms=0.770778) #GCMRL# 91 dt 0.003000 rms 0.771 0.000% neg 0 invalid 762 tFOTS 14.7050 tGradient 2.8370 tsec 18.7390 GCAMregister done in 20.6398 min Starting GCAmapRenormalizeWithAlignment() without scales renormalizing by structure alignment.... renormalizing input #0 gca peak = 0.10253 (16) mri peak = 0.17945 (29) Left_Lateral_Ventricle (4): linear fit = 1.60 x + 0.0 (2748 voxels, overlap=0.236) Left_Lateral_Ventricle (4): linear fit = 1.50 x + 0.0 (2748 voxels, peak = 26), gca=24.0 gca peak = 0.17690 (16) mri peak = 0.17888 (29) Right_Lateral_Ventricle (43): linear fit = 1.84 x + 0.0 (1828 voxels, overlap=0.094) Right_Lateral_Ventricle (43): linear fit = 1.50 x + 0.0 (1828 voxels, peak = 29), gca=24.0 gca peak = 0.28275 (96) mri peak = 0.11610 (99) Right_Pallidum (52): linear fit = 1.03 x + 0.0 (1064 voxels, overlap=0.900) Right_Pallidum (52): linear fit = 1.03 x + 0.0 (1064 voxels, peak = 99), gca=99.4 gca peak = 0.18948 (93) mri peak = 0.08981 (99) Left_Pallidum (13): linear fit = 1.05 x + 0.0 (946 voxels, overlap=0.644) Left_Pallidum (13): linear fit = 1.05 x + 0.0 (946 voxels, peak = 98), gca=98.1 gca peak = 0.20755 (55) mri peak = 0.10477 (72) Right_Hippocampus (53): linear fit = 1.26 x + 0.0 (1091 voxels, overlap=0.015) Right_Hippocampus (53): linear fit = 1.26 x + 0.0 (1091 voxels, peak = 70), gca=69.6 gca peak = 0.31831 (58) mri peak = 0.09818 (77) Left_Hippocampus (17): linear fit = 1.30 x + 0.0 (823 voxels, overlap=0.012) Left_Hippocampus (17): linear fit = 1.30 x + 0.0 (823 voxels, peak = 76), gca=75.7 gca peak = 0.11957 (102) mri peak = 0.10473 (106) Right_Cerebral_White_Matter (41): linear fit = 1.04 x + 0.0 (67586 voxels, overlap=0.711) Right_Cerebral_White_Matter (41): linear fit = 1.04 x + 0.0 (67586 voxels, peak = 107), gca=106.6 gca peak = 0.11429 (102) mri peak = 0.09554 (106) Left_Cerebral_White_Matter (2): linear fit = 1.04 x + 0.0 (70172 voxels, overlap=0.634) Left_Cerebral_White_Matter (2): linear fit = 1.04 x + 0.0 (70172 voxels, peak = 107), gca=106.6 gca peak = 0.14521 (59) mri peak = 0.03394 (87) Left_Cerebral_Cortex (3): linear fit = 1.43 x + 0.0 (24820 voxels, overlap=0.000) Left_Cerebral_Cortex (3): linear fit = 1.43 x + 0.0 (24820 voxels, peak = 85), gca=84.7 gca peak = 0.14336 (58) mri peak = 0.03736 (80) Right_Cerebral_Cortex (42): linear fit = 1.32 x + 0.0 (25166 voxels, overlap=0.000) Right_Cerebral_Cortex (42): linear fit = 1.32 x + 0.0 (25166 voxels, peak = 76), gca=76.3 gca peak = 0.13305 (70) mri peak = 0.11431 (78) Right_Caudate (50): linear fit = 1.15 x + 0.0 (1018 voxels, overlap=0.090) Right_Caudate (50): linear fit = 1.15 x + 0.0 (1018 voxels, peak = 81), gca=80.8 gca peak = 0.15761 (71) mri peak = 0.11060 (87) Left_Caudate (11): linear fit = 1.15 x + 0.0 (607 voxels, overlap=0.110) Left_Caudate (11): linear fit = 1.15 x + 0.0 (607 voxels, peak = 82), gca=82.0 gca peak = 0.13537 (57) mri peak = 0.04859 (69) Left_Cerebellum_Cortex (8): linear fit = 1.24 x + 0.0 (30636 voxels, overlap=0.005) Left_Cerebellum_Cortex (8): linear fit = 1.24 x + 0.0 (30636 voxels, peak = 70), gca=70.4 gca peak = 0.13487 (56) mri peak = 0.04516 (68) Right_Cerebellum_Cortex (47): linear fit = 1.21 x + 0.0 (34390 voxels, overlap=0.141) Right_Cerebellum_Cortex (47): linear fit = 1.21 x + 0.0 (34390 voxels, peak = 67), gca=67.5 gca peak = 0.19040 (84) mri peak = 0.10955 (84) Left_Cerebellum_White_Matter (7): linear fit = 1.02 x + 0.0 (11457 voxels, overlap=0.886) Left_Cerebellum_White_Matter (7): linear fit = 1.02 x + 0.0 (11457 voxels, peak = 86), gca=86.1 gca peak = 0.18871 (83) mri peak = 0.10712 (85) Right_Cerebellum_White_Matter (46): linear fit = 1.01 x + 0.0 (9569 voxels, overlap=0.889) Right_Cerebellum_White_Matter (46): linear fit = 1.01 x + 0.0 (9569 voxels, peak = 84), gca=84.2 gca peak = 0.24248 (57) mri peak = 0.10628 (78) Left_Amygdala (18): linear fit = 1.27 x + 0.0 (402 voxels, overlap=0.057) Left_Amygdala (18): linear fit = 1.27 x + 0.0 (402 voxels, peak = 73), gca=72.7 gca peak = 0.35833 (56) mri peak = 0.17241 (72) Right_Amygdala (54): linear fit = 1.27 x + 0.0 (636 voxels, overlap=0.025) Right_Amygdala (54): linear fit = 1.27 x + 0.0 (636 voxels, peak = 71), gca=71.4 gca peak = 0.12897 (85) mri peak = 0.09402 (94) Left_Thalamus (10): linear fit = 1.10 x + 0.0 (5276 voxels, overlap=0.489) Left_Thalamus (10): linear fit = 1.10 x + 0.0 (5276 voxels, peak = 93), gca=93.1 gca peak = 0.13127 (83) mri peak = 0.09539 (90) Right_Thalamus (49): linear fit = 1.08 x + 0.0 (4249 voxels, overlap=0.655) Right_Thalamus (49): linear fit = 1.08 x + 0.0 (4249 voxels, peak = 89), gca=89.2 gca peak = 0.12974 (78) mri peak = 0.09592 (91) Left_Putamen (12): linear fit = 1.14 x + 0.0 (2608 voxels, overlap=0.078) Left_Putamen (12): linear fit = 1.14 x + 0.0 (2608 voxels, peak = 89), gca=89.3 gca peak = 0.17796 (79) mri peak = 0.09592 (90) Right_Putamen (51): linear fit = 1.14 x + 0.0 (2849 voxels, overlap=0.021) Right_Putamen (51): linear fit = 1.14 x + 0.0 (2849 voxels, peak = 90), gca=90.5 gca peak = 0.10999 (80) mri peak = 0.12845 (81) Brain_Stem (16): linear fit = 1.07 x + 0.0 (14042 voxels, overlap=0.318) Brain_Stem (16): linear fit = 1.07 x + 0.0 (14042 voxels, peak = 85), gca=85.2 gca peak = 0.13215 (88) mri peak = 0.10216 (91) Right_VentralDC (60): linear fit = 1.09 x + 0.0 (1425 voxels, overlap=0.422) Right_VentralDC (60): linear fit = 1.09 x + 0.0 (1425 voxels, peak = 95), gca=95.5 gca peak = 0.11941 (89) mri peak = 0.08613 (90) Left_VentralDC (28): linear fit = 1.07 x + 0.0 (1462 voxels, overlap=0.616) Left_VentralDC (28): linear fit = 1.07 x + 0.0 (1462 voxels, peak = 95), gca=94.8 gca peak = 0.20775 (25) mri peak = 0.17334 (30) Third_Ventricle (14): linear fit = 1.25 x + 0.0 (74 voxels, overlap=0.322) Third_Ventricle (14): linear fit = 1.25 x + 0.0 (74 voxels, peak = 31), gca=31.4 gca peak = 0.13297 (21) mri peak = 0.16982 (26) Fourth_Ventricle (15): linear fit = 1.59 x + 0.0 (302 voxels, overlap=0.305) Fourth_Ventricle (15): linear fit = 1.59 x + 0.0 (302 voxels, peak = 33), gca=33.3 gca peak Unknown = 0.94777 ( 0) gca peak Left_Inf_Lat_Vent = 0.19087 (28) gca peak Fourth_Ventricle = 0.13297 (21) gca peak CSF = 0.16821 (33) gca peak Left_Accumbens_area = 0.32850 (63) gca peak Left_undetermined = 0.98480 (28) gca peak Left_vessel = 0.40887 (53) gca peak Left_choroid_plexus = 0.10898 (46) gca peak Right_Inf_Lat_Vent = 0.17798 (26) gca peak Right_Accumbens_area = 0.30137 (64) gca peak Right_vessel = 0.47828 (52) gca peak Right_choroid_plexus = 0.11612 (45) gca peak Fifth_Ventricle = 0.59466 (35) gca peak WM_hypointensities = 0.10053 (78) gca peak non_WM_hypointensities = 0.07253 (60) gca peak Optic_Chiasm = 0.25330 (73) not using caudate to estimate GM means estimating mean gm scale to be 1.31 x + 0.0 estimating mean wm scale to be 1.04 x + 0.0 estimating mean csf scale to be 1.42 x + 0.0 saving intensity scales to talairach.label_intensities.txt GCAmapRenormalizeWithAlignment() took 2.91807 min noneg pre Starting GCAMregister() label assignment complete, 0 changed (0.00%) npasses = 1, nlevels = 6 #pass# 1 of 1 ************************ enabling zero nodes setting smoothness cost coefficient to 0.008 #GCAMreg# pass 0 level1 5 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.01 tol=5.00e-02, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=256, sigma=2.0,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.860981 #FOTS# QuadFit found better minimum quadopt=(dt=142.872,rms=0.818546) vs oldopt=(dt=92.48,rms=0.824144) #GCMRL# 93 dt 142.871609 rms 0.819 4.929% neg 0 invalid 762 tFOTS 14.7290 tGradient 6.4610 tsec 22.3450 #FOTS# QuadFit found better minimum quadopt=(dt=443.904,rms=0.805275) vs oldopt=(dt=369.92,rms=0.805683) #GCMRL# 94 dt 443.904000 rms 0.805 1.621% neg 0 invalid 762 tFOTS 14.6910 tGradient 6.2710 tsec 22.1110 #FOTS# QuadFit found better minimum quadopt=(dt=443.904,rms=0.787822) vs oldopt=(dt=369.92,rms=0.788392) #GCMRL# 95 dt 443.904000 rms 0.788 2.167% neg 0 invalid 762 tFOTS 14.6940 tGradient 7.0030 tsec 22.8490 #GCMRL# 96 dt 92.480000 rms 0.786 0.289% neg 0 invalid 762 tFOTS 15.6120 tGradient 6.4050 tsec 23.1650 #FOTS# QuadFit found better minimum quadopt=(dt=129.472,rms=0.784649) vs oldopt=(dt=92.48,rms=0.784747) #GCMRL# 97 dt 129.472000 rms 0.785 0.114% neg 0 invalid 762 tFOTS 14.6970 tGradient 6.1920 tsec 22.0370 #FOTS# QuadFit found better minimum quadopt=(dt=1775.62,rms=0.774982) vs oldopt=(dt=1479.68,rms=0.775003) #GCMRL# 98 dt 1775.616000 rms 0.775 1.232% neg 0 invalid 762 tFOTS 14.6820 tGradient 6.3870 tsec 22.2200 #FOTS# QuadFit found better minimum quadopt=(dt=335.805,rms=0.76106) vs oldopt=(dt=369.92,rms=0.761162) #GCMRL# 99 dt 335.804695 rms 0.761 1.796% neg 0 invalid 762 tFOTS 16.5400 tGradient 6.8380 tsec 24.5260 #FOTS# QuadFit found better minimum quadopt=(dt=73.984,rms=0.760572) vs oldopt=(dt=92.48,rms=0.760617) #GCMRL# 100 dt 73.984000 rms 0.761 0.064% neg 0 invalid 762 tFOTS 15.5940 tGradient 6.6200 tsec 23.3610 #FOTS# QuadFit found better minimum quadopt=(dt=55.488,rms=0.760435) vs oldopt=(dt=92.48,rms=0.76046) #GCMRL# 101 dt 55.488000 rms 0.760 0.000% neg 0 invalid 762 tFOTS 15.6180 tGradient 6.5810 tsec 23.3850 #GCMRL# 102 dt 55.488000 rms 0.760 0.017% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5330 tsec 7.6820 #GCMRL# 103 dt 55.488000 rms 0.760 0.023% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5240 tsec 7.6740 #GCMRL# 104 dt 55.488000 rms 0.760 0.044% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5550 tsec 7.7040 #GCMRL# 105 dt 55.488000 rms 0.759 0.104% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5860 tsec 7.7360 #GCMRL# 106 dt 55.488000 rms 0.758 0.193% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5790 tsec 7.7280 #GCMRL# 107 dt 55.488000 rms 0.755 0.278% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5770 tsec 7.7310 #GCMRL# 108 dt 55.488000 rms 0.753 0.328% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5750 tsec 7.7240 #GCMRL# 109 dt 55.488000 rms 0.750 0.336% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6160 tsec 7.7660 #GCMRL# 110 dt 55.488000 rms 0.748 0.318% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6050 tsec 7.7590 #GCMRL# 111 dt 55.488000 rms 0.746 0.294% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6300 tsec 7.7810 #GCMRL# 112 dt 55.488000 rms 0.744 0.266% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6050 tsec 7.7560 #GCMRL# 113 dt 55.488000 rms 0.742 0.245% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5810 tsec 7.7290 #GCMRL# 114 dt 55.488000 rms 0.740 0.247% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5470 tsec 7.6960 #GCMRL# 115 dt 55.488000 rms 0.738 0.242% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.7380 tsec 7.8870 #GCMRL# 116 dt 55.488000 rms 0.737 0.249% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.7140 tsec 7.8650 #GCMRL# 117 dt 55.488000 rms 0.735 0.262% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.8350 tsec 7.9840 #GCMRL# 118 dt 55.488000 rms 0.733 0.262% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.8280 tsec 7.9780 #GCMRL# 119 dt 55.488000 rms 0.731 0.257% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.8040 tsec 7.9550 #GCMRL# 120 dt 55.488000 rms 0.729 0.246% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.7950 tsec 7.9440 #GCMRL# 121 dt 55.488000 rms 0.727 0.233% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.8490 tsec 8.0010 #GCMRL# 122 dt 55.488000 rms 0.726 0.214% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6360 tsec 7.7870 #GCMRL# 123 dt 55.488000 rms 0.724 0.201% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6980 tsec 7.8480 #GCMRL# 124 dt 55.488000 rms 0.723 0.189% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6460 tsec 7.7990 #GCMRL# 125 dt 55.488000 rms 0.722 0.184% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6190 tsec 7.7670 #GCMRL# 126 dt 55.488000 rms 0.720 0.176% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6360 tsec 7.7860 #GCMRL# 127 dt 55.488000 rms 0.719 0.166% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6370 tsec 7.7850 #GCMRL# 128 dt 55.488000 rms 0.718 0.159% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6180 tsec 7.7680 #GCMRL# 129 dt 55.488000 rms 0.717 0.152% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5540 tsec 7.7020 #GCMRL# 130 dt 55.488000 rms 0.716 0.150% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6420 tsec 7.7910 #GCMRL# 131 dt 55.488000 rms 0.715 0.146% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5250 tsec 7.6780 #GCMRL# 132 dt 55.488000 rms 0.714 0.143% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6320 tsec 7.7810 #GCMRL# 133 dt 55.488000 rms 0.713 0.137% neg 0 invalid 762 tFOTS 0.0000 tGradient 7.0070 tsec 8.1580 #GCMRL# 134 dt 55.488000 rms 0.712 0.132% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.9410 tsec 8.0890 #GCMRL# 135 dt 55.488000 rms 0.711 0.126% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6780 tsec 7.8270 #GCMRL# 136 dt 55.488000 rms 0.710 0.121% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6760 tsec 7.8240 #GCMRL# 137 dt 55.488000 rms 0.709 0.116% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6810 tsec 7.8310 #GCMRL# 138 dt 55.488000 rms 0.708 0.114% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.7010 tsec 7.8530 #GCMRL# 139 dt 55.488000 rms 0.708 0.109% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6920 tsec 7.8430 #GCMRL# 140 dt 55.488000 rms 0.707 0.106% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.7240 tsec 7.8740 #GCMRL# 141 dt 55.488000 rms 0.706 0.103% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6190 tsec 7.7680 #GCMRL# 142 dt 55.488000 rms 0.705 0.103% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.7850 tsec 7.9350 #GCMRL# 143 dt 55.488000 rms 0.705 0.104% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.7560 tsec 7.9060 #GCMRL# 144 dt 55.488000 rms 0.704 0.101% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6740 tsec 7.8230 #GCMRL# 145 dt 55.488000 rms 0.703 0.098% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.7270 tsec 7.8770 #GCMRL# 146 dt 55.488000 rms 0.703 0.094% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5800 tsec 7.7300 #GCMRL# 147 dt 55.488000 rms 0.702 0.090% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5480 tsec 7.6970 #GCMRL# 148 dt 55.488000 rms 0.701 0.086% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5300 tsec 7.6820 #GCMRL# 149 dt 55.488000 rms 0.701 0.083% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5660 tsec 7.7150 #GCMRL# 150 dt 55.488000 rms 0.700 0.081% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4680 tsec 7.6180 #GCMRL# 151 dt 55.488000 rms 0.700 0.078% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4690 tsec 7.6190 #GCMRL# 152 dt 55.488000 rms 0.699 0.076% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5000 tsec 7.6520 #GCMRL# 153 dt 55.488000 rms 0.699 0.075% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5080 tsec 7.6560 #GCMRL# 154 dt 55.488000 rms 0.698 0.072% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4800 tsec 7.6300 #GCMRL# 155 dt 55.488000 rms 0.698 0.071% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4700 tsec 7.6170 #GCMRL# 156 dt 55.488000 rms 0.697 0.068% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4430 tsec 7.5920 #GCMRL# 157 dt 55.488000 rms 0.697 0.066% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4680 tsec 7.6180 #GCMRL# 158 dt 55.488000 rms 0.696 0.064% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4360 tsec 7.5860 #GCMRL# 159 dt 55.488000 rms 0.696 0.062% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4540 tsec 7.6050 #GCMRL# 160 dt 55.488000 rms 0.695 0.060% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4440 tsec 7.6000 #GCMRL# 161 dt 55.488000 rms 0.695 0.059% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4180 tsec 7.5730 #GCMRL# 162 dt 55.488000 rms 0.695 0.059% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4190 tsec 7.5700 #GCMRL# 163 dt 55.488000 rms 0.694 0.058% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4400 tsec 7.5890 #GCMRL# 164 dt 55.488000 rms 0.694 0.056% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4460 tsec 7.5970 #GCMRL# 165 dt 55.488000 rms 0.693 0.055% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4510 tsec 7.6000 #GCMRL# 166 dt 55.488000 rms 0.693 0.053% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4420 tsec 7.5910 #GCMRL# 167 dt 55.488000 rms 0.693 0.052% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4250 tsec 7.5810 #GCMRL# 168 dt 55.488000 rms 0.692 0.050% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4190 tsec 7.5720 #GCMRL# 169 dt 55.488000 rms 0.692 0.049% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4120 tsec 7.5660 #GCMRL# 170 dt 55.488000 rms 0.692 0.049% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4480 tsec 7.5970 #GCMRL# 171 dt 55.488000 rms 0.691 0.050% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4250 tsec 7.5740 #GCMRL# 172 dt 55.488000 rms 0.691 0.047% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4200 tsec 7.5700 #GCMRL# 173 dt 55.488000 rms 0.691 0.046% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4400 tsec 7.5890 #GCMRL# 174 dt 55.488000 rms 0.690 0.045% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4390 tsec 7.5880 #GCMRL# 175 dt 55.488000 rms 0.690 0.045% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4740 tsec 7.6250 #GCMRL# 176 dt 55.488000 rms 0.690 0.044% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4840 tsec 7.6320 #GCMRL# 177 dt 55.488000 rms 0.690 0.042% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4860 tsec 7.6380 #GCMRL# 178 dt 55.488000 rms 0.689 0.045% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4420 tsec 7.5910 #GCMRL# 179 dt 55.488000 rms 0.689 0.043% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4220 tsec 7.5700 #GCMRL# 180 dt 55.488000 rms 0.689 0.042% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4250 tsec 7.5830 #GCMRL# 181 dt 55.488000 rms 0.688 0.041% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4370 tsec 7.5860 #GCMRL# 182 dt 55.488000 rms 0.688 0.041% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4150 tsec 7.5650 #GCMRL# 183 dt 55.488000 rms 0.688 0.040% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4730 tsec 7.6210 #GCMRL# 184 dt 55.488000 rms 0.688 0.039% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4250 tsec 7.5740 #GCMRL# 185 dt 55.488000 rms 0.687 0.040% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.3580 tsec 7.5100 #GCMRL# 186 dt 55.488000 rms 0.687 0.039% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4500 tsec 7.5990 #GCMRL# 187 dt 55.488000 rms 0.687 0.039% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4400 tsec 7.5890 #GCMRL# 188 dt 55.488000 rms 0.686 0.038% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4420 tsec 7.5930 #GCMRL# 189 dt 55.488000 rms 0.686 0.037% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4340 tsec 7.5880 #GCMRL# 190 dt 55.488000 rms 0.686 0.037% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4320 tsec 7.5810 #GCMRL# 191 dt 55.488000 rms 0.686 0.035% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5170 tsec 7.6670 #GCMRL# 192 dt 55.488000 rms 0.685 0.036% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4240 tsec 7.5760 #GCMRL# 193 dt 55.488000 rms 0.685 0.039% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4180 tsec 7.5710 #GCMRL# 194 dt 55.488000 rms 0.685 0.038% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4410 tsec 7.5900 #GCMRL# 195 dt 55.488000 rms 0.685 0.037% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4510 tsec 7.6030 #GCMRL# 196 dt 55.488000 rms 0.684 0.036% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4830 tsec 7.6410 #GCMRL# 197 dt 55.488000 rms 0.684 0.034% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4770 tsec 7.6280 #GCMRL# 198 dt 55.488000 rms 0.684 0.035% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.6280 tsec 7.7790 #GCMRL# 199 dt 55.488000 rms 0.684 0.033% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5860 tsec 7.7350 #GCMRL# 200 dt 55.488000 rms 0.684 0.033% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5070 tsec 7.6590 #GCMRL# 201 dt 55.488000 rms 0.683 0.032% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4930 tsec 7.6430 #GCMRL# 202 dt 55.488000 rms 0.683 0.031% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5220 tsec 7.6740 #GCMRL# 203 dt 55.488000 rms 0.683 0.031% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5030 tsec 7.6550 #GCMRL# 204 dt 55.488000 rms 0.683 0.029% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4300 tsec 7.5800 #GCMRL# 205 dt 55.488000 rms 0.682 0.030% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4350 tsec 7.5840 #GCMRL# 206 dt 55.488000 rms 0.682 0.029% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4250 tsec 7.5780 #GCMRL# 207 dt 55.488000 rms 0.682 0.029% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4510 tsec 7.6000 #GCMRL# 208 dt 55.488000 rms 0.682 0.028% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4260 tsec 7.5760 #GCMRL# 209 dt 55.488000 rms 0.682 0.027% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5000 tsec 7.6500 #GCMRL# 210 dt 55.488000 rms 0.682 0.027% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5090 tsec 7.6620 #GCMRL# 211 dt 55.488000 rms 0.681 0.027% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5030 tsec 7.6520 #GCMRL# 212 dt 55.488000 rms 0.681 0.028% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4860 tsec 7.6350 #GCMRL# 213 dt 55.488000 rms 0.681 0.028% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5180 tsec 7.6670 #GCMRL# 214 dt 55.488000 rms 0.681 0.028% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5080 tsec 7.6570 #GCMRL# 215 dt 55.488000 rms 0.681 0.027% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4730 tsec 7.6210 #GCMRL# 216 dt 55.488000 rms 0.680 0.027% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5370 tsec 7.6860 #GCMRL# 217 dt 55.488000 rms 0.680 0.026% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5360 tsec 7.6850 #GCMRL# 218 dt 55.488000 rms 0.680 0.026% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5320 tsec 7.6820 #GCMRL# 219 dt 55.488000 rms 0.680 0.026% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5570 tsec 7.7080 #GCMRL# 220 dt 55.488000 rms 0.680 0.025% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5550 tsec 7.7030 #GCMRL# 221 dt 55.488000 rms 0.680 0.025% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5330 tsec 7.6840 #GCMRL# 222 dt 55.488000 rms 0.679 0.024% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5140 tsec 7.7000 #GCMRL# 223 dt 23674.880000 rms 0.677 0.384% neg 0 invalid 762 tFOTS 16.5220 tGradient 6.5010 tsec 24.1720 #FOTS# QuadFit found better minimum quadopt=(dt=129.472,rms=0.674442) vs oldopt=(dt=92.48,rms=0.674869) #GCMRL# 224 dt 129.472000 rms 0.674 0.340% neg 0 invalid 762 tFOTS 13.7950 tGradient 6.5770 tsec 21.5190 #FOTS# QuadFit found better minimum quadopt=(dt=443.904,rms=0.673784) vs oldopt=(dt=369.92,rms=0.673792) #GCMRL# 225 dt 443.904000 rms 0.674 0.098% neg 0 invalid 762 tFOTS 14.6930 tGradient 6.8880 tsec 22.7290 #FOTS# QuadFit found better minimum quadopt=(dt=129.472,rms=0.673286) vs oldopt=(dt=92.48,rms=0.673379) #GCMRL# 226 dt 129.472000 rms 0.673 0.074% neg 0 invalid 762 tFOTS 15.6050 tGradient 6.8570 tsec 23.6110 #GCMRL# 227 dt 0.850000 rms 0.673 0.000% neg 0 invalid 762 tFOTS 16.5150 tGradient 6.3560 tsec 25.0960 #GCAMreg# pass 0 level1 5 level2 1 tsec 1267.44 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.01 tol=5.00e-02, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=256, sigma=0.5,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.674021 #FOTS# QuadFit found better minimum quadopt=(dt=129.472,rms=0.672974) vs oldopt=(dt=92.48,rms=0.673024) #GCMRL# 229 dt 129.472000 rms 0.673 0.155% neg 0 invalid 762 tFOTS 15.6190 tGradient 6.3520 tsec 23.1190 #FOTS# QuadFit found better minimum quadopt=(dt=443.904,rms=0.672258) vs oldopt=(dt=369.92,rms=0.672291) #GCMRL# 230 dt 443.904000 rms 0.672 0.106% neg 0 invalid 762 tFOTS 15.6190 tGradient 6.4580 tsec 23.2270 #GCMRL# 231 dt 369.920000 rms 0.672 0.000% neg 0 invalid 762 tFOTS 15.6130 tGradient 6.4890 tsec 23.2870 #GCMRL# 232 dt 369.920000 rms 0.672 0.062% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.5110 tsec 7.6610 #GCMRL# 233 dt 369.920000 rms 0.671 0.043% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4280 tsec 7.5790 #GCMRL# 234 dt 369.920000 rms 0.671 0.048% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4300 tsec 7.5800 #GCMRL# 235 dt 369.920000 rms 0.670 0.072% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.4360 tsec 7.5840 #GCMRL# 236 dt 369.920000 rms 0.670 0.052% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.3920 tsec 7.5420 #GCMRL# 237 dt 369.920000 rms 0.670 0.035% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.3860 tsec 7.5360 #GCMRL# 238 dt 369.920000 rms 0.670 0.019% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.3580 tsec 7.5060 #GCMRL# 239 dt 369.920000 rms 0.670 0.025% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.3810 tsec 7.5330 #GCMRL# 240 dt 369.920000 rms 0.669 0.021% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.3700 tsec 7.5570 #FOTS# QuadFit found better minimum quadopt=(dt=221.952,rms=0.669329) vs oldopt=(dt=369.92,rms=0.669353) #GCMRL# 241 dt 221.952000 rms 0.669 0.000% neg 0 invalid 762 tFOTS 16.5360 tGradient 6.3980 tsec 24.1210 #GCMRL# 242 dt 221.952000 rms 0.669 0.013% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.3680 tsec 7.5210 #GCMRL# 243 dt 221.952000 rms 0.669 0.018% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.3670 tsec 7.5170 #GCMRL# 244 dt 221.952000 rms 0.669 0.017% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.3710 tsec 7.5190 setting smoothness cost coefficient to 0.031 #GCAMreg# pass 0 level1 4 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.03 tol=5.00e-02, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=64, sigma=2.0,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.673087 #FOTS# QuadFit found better minimum quadopt=(dt=188.981,rms=0.665412) vs oldopt=(dt=103.68,rms=0.666722) #GCMRL# 246 dt 188.981132 rms 0.665 1.140% neg 0 invalid 762 tFOTS 14.6870 tGradient 4.8260 tsec 20.6610 #FOTS# QuadFit found better minimum quadopt=(dt=140.518,rms=0.658091) vs oldopt=(dt=103.68,rms=0.658562) #GCMRL# 247 dt 140.518337 rms 0.658 1.100% neg 0 invalid 762 tFOTS 15.6010 tGradient 5.2620 tsec 22.0160 #FOTS# QuadFit found better minimum quadopt=(dt=91.3994,rms=0.652792) vs oldopt=(dt=103.68,rms=0.652898) #GCMRL# 248 dt 91.399361 rms 0.653 0.805% neg 0 invalid 762 tFOTS 14.6950 tGradient 4.8710 tsec 20.7140 #FOTS# QuadFit found better minimum quadopt=(dt=120.402,rms=0.649837) vs oldopt=(dt=103.68,rms=0.649876) #GCMRL# 249 dt 120.401826 rms 0.650 0.453% neg 0 invalid 762 tFOTS 15.6180 tGradient 5.1300 tsec 21.8960 #FOTS# QuadFit found better minimum quadopt=(dt=107.415,rms=0.645881) vs oldopt=(dt=103.68,rms=0.645883) #GCMRL# 250 dt 107.415205 rms 0.646 0.609% neg 0 invalid 762 tFOTS 14.6860 tGradient 4.7800 tsec 20.6140 #FOTS# QuadFit found better minimum quadopt=(dt=83.2621,rms=0.64369) vs oldopt=(dt=103.68,rms=0.643831) #GCMRL# 251 dt 83.262136 rms 0.644 0.339% neg 0 invalid 762 tFOTS 15.6040 tGradient 5.1920 tsec 21.9450 #FOTS# QuadFit found better minimum quadopt=(dt=145.152,rms=0.640236) vs oldopt=(dt=103.68,rms=0.64071) #GCMRL# 252 dt 145.152000 rms 0.640 0.537% neg 0 invalid 762 tFOTS 13.7850 tGradient 4.7990 tsec 19.7340 #FOTS# QuadFit found better minimum quadopt=(dt=71.9477,rms=0.638364) vs oldopt=(dt=103.68,rms=0.638652) #GCMRL# 253 dt 71.947712 rms 0.638 0.292% neg 0 invalid 762 tFOTS 15.6110 tGradient 4.8350 tsec 21.5940 #FOTS# QuadFit found better minimum quadopt=(dt=145.152,rms=0.63546) vs oldopt=(dt=103.68,rms=0.636028) #GCMRL# 254 dt 145.152000 rms 0.635 0.455% neg 0 invalid 762 tFOTS 14.6940 tGradient 4.8080 tsec 20.6520 #FOTS# QuadFit found better minimum quadopt=(dt=90.4431,rms=0.633972) vs oldopt=(dt=103.68,rms=0.634002) #GCMRL# 255 dt 90.443114 rms 0.634 0.234% neg 0 invalid 762 tFOTS 15.6050 tGradient 4.9440 tsec 21.6970 #FOTS# QuadFit found better minimum quadopt=(dt=124.416,rms=0.631901) vs oldopt=(dt=103.68,rms=0.631979) #GCMRL# 256 dt 124.416000 rms 0.632 0.327% neg 0 invalid 762 tFOTS 14.6890 tGradient 4.8140 tsec 20.6550 #FOTS# QuadFit found better minimum quadopt=(dt=70.8465,rms=0.630642) vs oldopt=(dt=103.68,rms=0.630842) #GCMRL# 257 dt 70.846512 rms 0.631 0.199% neg 0 invalid 762 tFOTS 15.5980 tGradient 4.9450 tsec 21.6920 #FOTS# QuadFit found better minimum quadopt=(dt=145.152,rms=0.628495) vs oldopt=(dt=103.68,rms=0.628901) #GCMRL# 258 dt 145.152000 rms 0.628 0.340% neg 0 invalid 762 tFOTS 14.6940 tGradient 5.0960 tsec 20.9380 #FOTS# QuadFit found better minimum quadopt=(dt=82.944,rms=0.627531) vs oldopt=(dt=103.68,rms=0.627566) #GCMRL# 259 dt 82.944000 rms 0.628 0.153% neg 0 invalid 762 tFOTS 15.6000 tGradient 4.9320 tsec 21.6810 #FOTS# QuadFit found better minimum quadopt=(dt=145.152,rms=0.625777) vs oldopt=(dt=103.68,rms=0.625995) #GCMRL# 260 dt 145.152000 rms 0.626 0.279% neg 0 invalid 762 tFOTS 14.6970 tGradient 5.0210 tsec 20.8670 #FOTS# QuadFit found better minimum quadopt=(dt=66.087,rms=0.624839) vs oldopt=(dt=103.68,rms=0.625094) #GCMRL# 261 dt 66.086957 rms 0.625 0.150% neg 0 invalid 762 tFOTS 15.6090 tGradient 4.9290 tsec 21.6870 #FOTS# QuadFit found better minimum quadopt=(dt=331.776,rms=0.622529) vs oldopt=(dt=414.72,rms=0.622766) #GCMRL# 262 dt 331.776000 rms 0.623 0.370% neg 0 invalid 762 tFOTS 14.6970 tGradient 4.9160 tsec 20.7610 #FOTS# QuadFit found better minimum quadopt=(dt=36.288,rms=0.620897) vs oldopt=(dt=25.92,rms=0.621237) #GCMRL# 263 dt 36.288000 rms 0.621 0.262% neg 0 invalid 762 tFOTS 15.6020 tGradient 4.8940 tsec 21.6450 #GCMRL# 264 dt 103.680000 rms 0.620 0.123% neg 0 invalid 762 tFOTS 15.6040 tGradient 4.9380 tsec 21.6950 #GCMRL# 265 dt 103.680000 rms 0.619 0.175% neg 0 invalid 762 tFOTS 14.6920 tGradient 4.8850 tsec 20.7290 #FOTS# QuadFit found better minimum quadopt=(dt=62.208,rms=0.618437) vs oldopt=(dt=103.68,rms=0.61855) #GCMRL# 266 dt 62.208000 rms 0.618 0.099% neg 0 invalid 762 tFOTS 14.7080 tGradient 4.8650 tsec 20.7230 #FOTS# QuadFit found better minimum quadopt=(dt=497.664,rms=0.616146) vs oldopt=(dt=414.72,rms=0.616156) #GCMRL# 267 dt 497.664000 rms 0.616 0.370% neg 0 invalid 762 tFOTS 14.6900 tGradient 5.0770 tsec 20.9180 #FOTS# QuadFit found better minimum quadopt=(dt=36.288,rms=0.614375) vs oldopt=(dt=25.92,rms=0.614734) #GCMRL# 268 dt 36.288000 rms 0.614 0.287% neg 0 invalid 762 tFOTS 15.6010 tGradient 5.0500 tsec 21.8000 #FOTS# QuadFit found better minimum quadopt=(dt=62.208,rms=0.613792) vs oldopt=(dt=103.68,rms=0.613884) #GCMRL# 269 dt 62.208000 rms 0.614 0.095% neg 0 invalid 762 tFOTS 14.6890 tGradient 5.0070 tsec 20.8480 #GCMRL# 270 dt 414.720000 rms 0.612 0.303% neg 0 invalid 762 tFOTS 14.6890 tGradient 5.0660 tsec 20.9030 #FOTS# QuadFit found better minimum quadopt=(dt=36.288,rms=0.610907) vs oldopt=(dt=25.92,rms=0.611109) #GCMRL# 271 dt 36.288000 rms 0.611 0.167% neg 0 invalid 762 tFOTS 15.5940 tGradient 5.0980 tsec 21.8440 #FOTS# QuadFit found better minimum quadopt=(dt=62.208,rms=0.610517) vs oldopt=(dt=103.68,rms=0.610562) #GCMRL# 272 dt 62.208000 rms 0.611 0.064% neg 0 invalid 762 tFOTS 14.7140 tGradient 5.0340 tsec 20.8950 #FOTS# QuadFit found better minimum quadopt=(dt=580.608,rms=0.608109) vs oldopt=(dt=414.72,rms=0.60846) #GCMRL# 273 dt 580.608000 rms 0.608 0.395% neg 0 invalid 762 tFOTS 14.6930 tGradient 5.0430 tsec 20.8900 #FOTS# QuadFit found better minimum quadopt=(dt=36.288,rms=0.607097) vs oldopt=(dt=25.92,rms=0.607297) #GCMRL# 274 dt 36.288000 rms 0.607 0.166% neg 0 invalid 762 tFOTS 15.6020 tGradient 5.0020 tsec 21.7590 #FOTS# QuadFit found better minimum quadopt=(dt=82.944,rms=0.606714) vs oldopt=(dt=103.68,rms=0.606746) #GCMRL# 275 dt 82.944000 rms 0.607 0.063% neg 0 invalid 762 tFOTS 14.6980 tGradient 4.9420 tsec 20.7900 #FOTS# QuadFit found better minimum quadopt=(dt=145.152,rms=0.605889) vs oldopt=(dt=103.68,rms=0.605986) #GCMRL# 276 dt 145.152000 rms 0.606 0.136% neg 0 invalid 762 tFOTS 13.7860 tGradient 4.9200 tsec 19.8540 #FOTS# QuadFit found better minimum quadopt=(dt=36.288,rms=0.605671) vs oldopt=(dt=25.92,rms=0.605725) #GCMRL# 277 dt 36.288000 rms 0.606 0.000% neg 0 invalid 762 tFOTS 15.6010 tGradient 4.9430 tsec 21.7300 #GCMRL# 278 dt 36.288000 rms 0.605 0.037% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.9680 tsec 6.1280 #GCMRL# 279 dt 36.288000 rms 0.605 0.051% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.9440 tsec 6.0910 #GCMRL# 280 dt 36.288000 rms 0.605 0.032% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.9460 tsec 6.6030 #GCMRL# 281 dt 18.144000 rms 0.605 0.015% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.9460 tsec 7.0700 #GCMRL# 282 dt 4.536000 rms 0.605 0.003% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.9740 tsec 7.5990 #FOTS# QuadFit found better minimum quadopt=(dt=0.14175,rms=0.604835) vs oldopt=(dt=0.10125,rms=0.604835) #GCMRL# 283 dt 0.141750 rms 0.605 0.000% neg 0 invalid 762 tFOTS 10.1340 tGradient 4.9930 tsec 16.3120 #GCMRL# 284 dt 0.141750 rms 0.605 0.000% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.9700 tsec 6.1210 #GCMRL# 285 dt 0.070875 rms 0.605 0.000% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.9710 tsec 7.0910 #GCAMreg# pass 0 level1 4 level2 1 tsec 752.476 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.03 tol=5.00e-02, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=64, sigma=0.5,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.605385 #GCMRL# 287 dt 103.680000 rms 0.604 0.307% neg 0 invalid 762 tFOTS 14.6910 tGradient 4.9890 tsec 20.8320 #GCMRL# 288 dt 103.680000 rms 0.602 0.220% neg 0 invalid 762 tFOTS 13.7770 tGradient 4.8060 tsec 19.7370 #FOTS# QuadFit found better minimum quadopt=(dt=124.416,rms=0.601904) vs oldopt=(dt=103.68,rms=0.601913) #GCMRL# 289 dt 124.416000 rms 0.602 0.000% neg 0 invalid 762 tFOTS 15.6190 tGradient 4.8150 tsec 21.6240 #GCMRL# 290 dt 62.208000 rms 0.601 0.118% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.9730 tsec 7.0960 #GCMRL# 291 dt 62.208000 rms 0.601 0.044% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8270 tsec 6.4810 #GCMRL# 292 dt 62.208000 rms 0.600 0.096% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7790 tsec 5.9340 #GCMRL# 293 dt 62.208000 rms 0.599 0.147% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8340 tsec 5.9820 #GCMRL# 294 dt 62.208000 rms 0.598 0.168% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8030 tsec 5.9530 #GCMRL# 295 dt 62.208000 rms 0.597 0.174% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7790 tsec 5.9320 #GCMRL# 296 dt 62.208000 rms 0.596 0.174% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7860 tsec 5.9380 #GCMRL# 297 dt 62.208000 rms 0.595 0.185% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7770 tsec 5.9280 #GCMRL# 298 dt 62.208000 rms 0.594 0.199% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.9150 tsec 6.0640 #GCMRL# 299 dt 62.208000 rms 0.593 0.204% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8050 tsec 5.9570 #GCMRL# 300 dt 62.208000 rms 0.592 0.198% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8600 tsec 6.0090 #GCMRL# 301 dt 62.208000 rms 0.591 0.184% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7570 tsec 5.9080 #GCMRL# 302 dt 62.208000 rms 0.590 0.183% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.6750 tsec 5.8290 #GCMRL# 303 dt 62.208000 rms 0.588 0.187% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7310 tsec 5.8810 #GCMRL# 304 dt 62.208000 rms 0.587 0.175% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7120 tsec 5.8630 #GCMRL# 305 dt 62.208000 rms 0.586 0.165% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7750 tsec 5.9240 #GCMRL# 306 dt 62.208000 rms 0.585 0.163% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8060 tsec 5.9540 #GCMRL# 307 dt 62.208000 rms 0.585 0.161% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7270 tsec 5.8780 #GCMRL# 308 dt 62.208000 rms 0.584 0.165% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7580 tsec 5.9080 #GCMRL# 309 dt 62.208000 rms 0.583 0.150% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7820 tsec 5.9300 #GCMRL# 310 dt 62.208000 rms 0.582 0.137% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7300 tsec 5.8780 #GCMRL# 311 dt 62.208000 rms 0.581 0.124% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7330 tsec 5.8810 #GCMRL# 312 dt 62.208000 rms 0.580 0.129% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7280 tsec 5.8760 #GCMRL# 313 dt 62.208000 rms 0.580 0.127% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7320 tsec 5.8810 #GCMRL# 314 dt 62.208000 rms 0.579 0.122% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7630 tsec 5.9120 #GCMRL# 315 dt 62.208000 rms 0.578 0.111% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7570 tsec 5.9090 #GCMRL# 316 dt 62.208000 rms 0.578 0.109% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7550 tsec 5.9090 #GCMRL# 317 dt 62.208000 rms 0.577 0.108% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7560 tsec 5.9060 #GCMRL# 318 dt 62.208000 rms 0.577 0.095% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8130 tsec 5.9630 #GCMRL# 319 dt 62.208000 rms 0.576 0.085% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8360 tsec 5.9880 #GCMRL# 320 dt 62.208000 rms 0.576 0.079% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8120 tsec 5.9620 #GCMRL# 321 dt 62.208000 rms 0.575 0.087% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8210 tsec 5.9720 #GCMRL# 322 dt 62.208000 rms 0.575 0.097% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7270 tsec 5.8750 #GCMRL# 323 dt 62.208000 rms 0.574 0.093% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8620 tsec 6.0110 #GCMRL# 324 dt 62.208000 rms 0.574 0.084% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8330 tsec 5.9850 #GCMRL# 325 dt 62.208000 rms 0.573 0.078% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7520 tsec 5.9010 #GCMRL# 326 dt 62.208000 rms 0.573 0.080% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7590 tsec 5.9080 #GCMRL# 327 dt 62.208000 rms 0.572 0.072% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7490 tsec 5.8980 #GCMRL# 328 dt 62.208000 rms 0.572 0.073% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8350 tsec 5.9910 #GCMRL# 329 dt 62.208000 rms 0.571 0.065% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8310 tsec 5.9830 #GCMRL# 330 dt 62.208000 rms 0.571 0.073% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7730 tsec 5.9210 #GCMRL# 331 dt 62.208000 rms 0.571 0.066% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7510 tsec 5.9010 #GCMRL# 332 dt 62.208000 rms 0.570 0.059% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8510 tsec 6.0000 #GCMRL# 333 dt 62.208000 rms 0.570 0.053% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7440 tsec 5.8970 #GCMRL# 334 dt 62.208000 rms 0.570 0.058% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7510 tsec 5.9020 #GCMRL# 335 dt 62.208000 rms 0.569 0.059% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7530 tsec 5.9020 #GCMRL# 336 dt 62.208000 rms 0.569 0.046% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7420 tsec 5.8910 #GCMRL# 337 dt 62.208000 rms 0.569 0.037% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7500 tsec 5.8990 #GCMRL# 338 dt 62.208000 rms 0.569 0.046% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7700 tsec 5.9210 #GCMRL# 339 dt 62.208000 rms 0.568 0.050% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7440 tsec 5.8940 #GCMRL# 340 dt 62.208000 rms 0.568 0.049% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7590 tsec 5.9090 #GCMRL# 341 dt 62.208000 rms 0.568 0.050% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7820 tsec 5.9310 #GCMRL# 342 dt 62.208000 rms 0.567 0.046% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7590 tsec 5.9090 #GCMRL# 343 dt 62.208000 rms 0.567 0.047% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7530 tsec 5.9050 #GCMRL# 344 dt 62.208000 rms 0.567 0.040% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7540 tsec 5.9030 #GCMRL# 345 dt 62.208000 rms 0.567 0.037% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7590 tsec 5.9080 #GCMRL# 346 dt 62.208000 rms 0.567 0.032% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7520 tsec 5.9040 #GCMRL# 347 dt 62.208000 rms 0.566 0.035% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7720 tsec 5.9220 #GCMRL# 348 dt 62.208000 rms 0.566 0.046% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7590 tsec 5.9070 #GCMRL# 349 dt 62.208000 rms 0.566 0.043% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7630 tsec 5.9140 #GCMRL# 350 dt 62.208000 rms 0.566 0.035% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7480 tsec 5.9020 #GCMRL# 351 dt 62.208000 rms 0.565 0.031% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7680 tsec 5.9190 #GCMRL# 352 dt 62.208000 rms 0.565 0.037% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7530 tsec 5.9050 #GCMRL# 353 dt 62.208000 rms 0.565 0.037% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7500 tsec 5.8990 #GCMRL# 354 dt 62.208000 rms 0.565 0.036% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8490 tsec 5.9970 #GCMRL# 355 dt 62.208000 rms 0.565 0.034% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8230 tsec 5.9720 #GCMRL# 356 dt 62.208000 rms 0.564 0.032% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8270 tsec 5.9820 #GCMRL# 357 dt 62.208000 rms 0.564 0.032% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8300 tsec 5.9780 #GCMRL# 358 dt 62.208000 rms 0.564 0.036% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8530 tsec 6.0040 #GCMRL# 359 dt 62.208000 rms 0.564 0.032% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8270 tsec 5.9760 #GCMRL# 360 dt 62.208000 rms 0.564 0.033% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8310 tsec 5.9810 #GCMRL# 361 dt 62.208000 rms 0.564 0.026% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8420 tsec 5.9950 #GCMRL# 362 dt 62.208000 rms 0.563 0.027% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8410 tsec 5.9930 #GCMRL# 363 dt 62.208000 rms 0.563 0.032% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8490 tsec 5.9980 #GCMRL# 364 dt 62.208000 rms 0.563 0.039% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8280 tsec 5.9770 #GCMRL# 365 dt 62.208000 rms 0.563 0.031% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8250 tsec 5.9760 #GCMRL# 366 dt 62.208000 rms 0.563 0.031% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.8230 tsec 5.9750 #GCMRL# 367 dt 62.208000 rms 0.563 0.024% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7440 tsec 5.8940 #GCMRL# 368 dt 62.208000 rms 0.562 0.023% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.7520 tsec 5.9390 #FOTS# QuadFit found better minimum quadopt=(dt=580.608,rms=0.562294) vs oldopt=(dt=414.72,rms=0.562303) #GCMRL# 369 dt 580.608000 rms 0.562 0.024% neg 0 invalid 762 tFOTS 15.6040 tGradient 4.7590 tsec 21.5160 #FOTS# QuadFit found better minimum quadopt=(dt=9.072,rms=0.562318) vs oldopt=(dt=6.48,rms=0.562318) setting smoothness cost coefficient to 0.118 #GCAMreg# pass 0 level1 3 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.12 tol=5.00e-02, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=16, sigma=2.0,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.576898 #FOTS# QuadFit found better minimum quadopt=(dt=25.6,rms=0.575323) vs oldopt=(dt=32,rms=0.57537) #GCMRL# 371 dt 25.600000 rms 0.575 0.273% neg 0 invalid 762 tFOTS 14.6900 tGradient 4.0120 tsec 19.8500 #FOTS# QuadFit found better minimum quadopt=(dt=38.4,rms=0.573219) vs oldopt=(dt=32,rms=0.573452) #GCMRL# 372 dt 38.400000 rms 0.573 0.366% neg 0 invalid 762 tFOTS 14.6940 tGradient 4.1740 tsec 20.0180 #FOTS# QuadFit found better minimum quadopt=(dt=38.4,rms=0.570907) vs oldopt=(dt=32,rms=0.571239) #GCMRL# 373 dt 38.400000 rms 0.571 0.403% neg 0 invalid 762 tFOTS 14.6920 tGradient 4.1490 tsec 19.9890 #FOTS# QuadFit found better minimum quadopt=(dt=44.8,rms=0.568206) vs oldopt=(dt=32,rms=0.56882) #GCMRL# 374 dt 44.800000 rms 0.568 0.473% neg 0 invalid 762 tFOTS 14.7000 tGradient 4.0140 tsec 19.8630 #FOTS# QuadFit found better minimum quadopt=(dt=11.2,rms=0.567494) vs oldopt=(dt=8,rms=0.567709) #GCMRL# 375 dt 11.200000 rms 0.567 0.125% neg 0 invalid 762 tFOTS 13.7840 tGradient 4.0620 tsec 18.9950 #FOTS# QuadFit found better minimum quadopt=(dt=44.8,rms=0.564897) vs oldopt=(dt=32,rms=0.565528) #GCMRL# 376 dt 44.800000 rms 0.565 0.458% neg 0 invalid 762 tFOTS 13.7850 tGradient 4.0850 tsec 19.0200 #FOTS# QuadFit found better minimum quadopt=(dt=44.8,rms=0.562719) vs oldopt=(dt=32,rms=0.563181) #GCMRL# 377 dt 44.800000 rms 0.563 0.385% neg 0 invalid 762 tFOTS 14.6880 tGradient 4.0040 tsec 19.8400 #FOTS# QuadFit found better minimum quadopt=(dt=11.2,rms=0.562136) vs oldopt=(dt=8,rms=0.562314) #GCMRL# 378 dt 11.200000 rms 0.562 0.104% neg 0 invalid 762 tFOTS 13.7810 tGradient 3.9860 tsec 18.9170 #GCMRL# 379 dt 32.000000 rms 0.561 0.279% neg 0 invalid 762 tFOTS 14.6900 tGradient 3.9940 tsec 19.8330 #FOTS# QuadFit found better minimum quadopt=(dt=44.8,rms=0.558713) vs oldopt=(dt=32,rms=0.559136) #GCMRL# 380 dt 44.800000 rms 0.559 0.331% neg 0 invalid 762 tFOTS 13.7800 tGradient 3.9860 tsec 18.9170 #FOTS# QuadFit found better minimum quadopt=(dt=11.2,rms=0.558275) vs oldopt=(dt=8,rms=0.55841) #GCMRL# 381 dt 11.200000 rms 0.558 0.078% neg 0 invalid 762 tFOTS 13.7830 tGradient 3.9930 tsec 18.9270 #GCMRL# 382 dt 32.000000 rms 0.557 0.229% neg 0 invalid 762 tFOTS 13.7790 tGradient 4.0660 tsec 18.9930 #FOTS# QuadFit found better minimum quadopt=(dt=11.2,rms=0.556495) vs oldopt=(dt=8,rms=0.556619) #GCMRL# 383 dt 11.200000 rms 0.556 0.090% neg 0 invalid 762 tFOTS 13.7840 tGradient 4.0690 tsec 19.0020 #FOTS# QuadFit found better minimum quadopt=(dt=44.8,rms=0.554943) vs oldopt=(dt=32,rms=0.555363) #GCMRL# 384 dt 44.800000 rms 0.555 0.279% neg 0 invalid 762 tFOTS 13.7820 tGradient 4.0650 tsec 18.9990 #FOTS# QuadFit found better minimum quadopt=(dt=44.8,rms=0.553678) vs oldopt=(dt=32,rms=0.553966) #GCMRL# 385 dt 44.800000 rms 0.554 0.228% neg 0 invalid 762 tFOTS 13.7870 tGradient 4.0630 tsec 18.9970 #FOTS# QuadFit found better minimum quadopt=(dt=11.2,rms=0.553238) vs oldopt=(dt=8,rms=0.553346) #GCMRL# 386 dt 11.200000 rms 0.553 0.080% neg 0 invalid 762 tFOTS 13.7870 tGradient 4.0670 tsec 19.0020 #FOTS# QuadFit found better minimum quadopt=(dt=44.8,rms=0.551892) vs oldopt=(dt=32,rms=0.552221) #GCMRL# 387 dt 44.800000 rms 0.552 0.243% neg 0 invalid 762 tFOTS 13.7900 tGradient 4.0650 tsec 19.0030 #FOTS# QuadFit found better minimum quadopt=(dt=38.4,rms=0.551288) vs oldopt=(dt=32,rms=0.55133) #GCMRL# 388 dt 38.400000 rms 0.551 0.110% neg 0 invalid 762 tFOTS 14.7020 tGradient 4.0630 tsec 19.9150 #FOTS# QuadFit found better minimum quadopt=(dt=11.2,rms=0.550749) vs oldopt=(dt=8,rms=0.550875) #GCMRL# 389 dt 11.200000 rms 0.551 0.098% neg 0 invalid 762 tFOTS 13.7920 tGradient 4.0710 tsec 19.0110 #GCMRL# 390 dt 32.000000 rms 0.550 0.173% neg 0 invalid 762 tFOTS 13.7810 tGradient 4.0710 tsec 19.0010 #FOTS# QuadFit found better minimum quadopt=(dt=38.4,rms=0.549198) vs oldopt=(dt=32,rms=0.549262) #GCMRL# 391 dt 38.400000 rms 0.549 0.108% neg 0 invalid 762 tFOTS 13.7900 tGradient 3.9790 tsec 18.9210 #GCMRL# 392 dt 32.000000 rms 0.548 0.143% neg 0 invalid 762 tFOTS 14.6950 tGradient 4.0370 tsec 19.8860 #FOTS# QuadFit found better minimum quadopt=(dt=38.4,rms=0.54779) vs oldopt=(dt=32,rms=0.547821) #GCMRL# 393 dt 38.400000 rms 0.548 0.114% neg 0 invalid 762 tFOTS 14.7100 tGradient 3.9760 tsec 19.8340 #FOTS# QuadFit found better minimum quadopt=(dt=38.4,rms=0.547052) vs oldopt=(dt=32,rms=0.547056) #GCMRL# 394 dt 38.400000 rms 0.547 0.135% neg 0 invalid 762 tFOTS 14.7020 tGradient 3.9820 tsec 19.8340 #GCMRL# 395 dt 32.000000 rms 0.546 0.123% neg 0 invalid 762 tFOTS 14.6990 tGradient 3.9610 tsec 19.8080 #FOTS# QuadFit found better minimum quadopt=(dt=38.4,rms=0.545676) vs oldopt=(dt=32,rms=0.545709) #GCMRL# 396 dt 38.400000 rms 0.546 0.128% neg 0 invalid 762 tFOTS 14.6920 tGradient 3.9570 tsec 19.7980 #FOTS# QuadFit found better minimum quadopt=(dt=25.6,rms=0.545214) vs oldopt=(dt=32,rms=0.545218) #GCMRL# 397 dt 25.600000 rms 0.545 0.085% neg 0 invalid 762 tFOTS 14.6980 tGradient 3.9570 tsec 19.8040 #FOTS# QuadFit found better minimum quadopt=(dt=44.8,rms=0.544451) vs oldopt=(dt=32,rms=0.544575) #GCMRL# 398 dt 44.800000 rms 0.544 0.140% neg 0 invalid 762 tFOTS 13.7890 tGradient 3.9560 tsec 18.8940 #FOTS# QuadFit found better minimum quadopt=(dt=25.6,rms=0.544145) vs oldopt=(dt=32,rms=0.544179) #GCMRL# 399 dt 25.600000 rms 0.544 0.056% neg 0 invalid 762 tFOTS 14.7080 tGradient 3.9540 tsec 19.8100 #FOTS# QuadFit found better minimum quadopt=(dt=44.8,rms=0.543388) vs oldopt=(dt=32,rms=0.543508) #GCMRL# 400 dt 44.800000 rms 0.543 0.139% neg 0 invalid 762 tFOTS 13.7850 tGradient 3.9550 tsec 18.8880 #FOTS# QuadFit found better minimum quadopt=(dt=25.6,rms=0.543135) vs oldopt=(dt=32,rms=0.543178) #GCMRL# 401 dt 25.600000 rms 0.543 0.000% neg 0 invalid 762 tFOTS 14.6950 tGradient 3.9730 tsec 19.8560 #GCMRL# 402 dt 25.600000 rms 0.543 0.094% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9730 tsec 5.1230 #GCMRL# 403 dt 25.600000 rms 0.542 0.121% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9660 tsec 5.1150 #GCMRL# 404 dt 25.600000 rms 0.541 0.152% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9590 tsec 5.1130 #GCMRL# 405 dt 25.600000 rms 0.540 0.184% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.0550 tsec 5.2070 #GCMRL# 406 dt 25.600000 rms 0.539 0.237% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9720 tsec 5.1220 #GCMRL# 407 dt 25.600000 rms 0.539 0.061% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9570 tsec 5.6120 #GCMRL# 408 dt 25.600000 rms 0.538 0.093% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9530 tsec 5.1030 #GCMRL# 409 dt 25.600000 rms 0.538 0.091% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.0360 tsec 5.1880 #GCMRL# 410 dt 25.600000 rms 0.537 0.125% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9540 tsec 5.1090 #GCMRL# 411 dt 25.600000 rms 0.536 0.161% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9520 tsec 5.1030 #GCMRL# 412 dt 25.600000 rms 0.535 0.190% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9510 tsec 5.1030 #GCMRL# 413 dt 25.600000 rms 0.534 0.179% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9520 tsec 5.1080 #GCMRL# 414 dt 25.600000 rms 0.533 0.171% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9510 tsec 5.1070 #GCMRL# 415 dt 25.600000 rms 0.532 0.191% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.0330 tsec 5.1850 #GCMRL# 416 dt 25.600000 rms 0.532 0.046% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.0340 tsec 5.6910 #GCMRL# 417 dt 25.600000 rms 0.532 0.008% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9640 tsec 5.6210 #GCMRL# 418 dt 25.600000 rms 0.532 0.037% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.0320 tsec 5.1840 #GCMRL# 419 dt 25.600000 rms 0.531 0.048% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9560 tsec 5.1090 #GCMRL# 420 dt 25.600000 rms 0.531 0.063% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9510 tsec 5.1050 #GCMRL# 421 dt 25.600000 rms 0.531 0.063% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9500 tsec 5.1030 #GCMRL# 422 dt 25.600000 rms 0.530 0.084% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.0290 tsec 5.1820 #GCMRL# 423 dt 25.600000 rms 0.530 0.094% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9490 tsec 5.1000 #GCMRL# 424 dt 25.600000 rms 0.529 0.095% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.8700 tsec 5.0220 #GCMRL# 425 dt 25.600000 rms 0.529 0.101% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9690 tsec 5.1190 #GCMRL# 426 dt 25.600000 rms 0.528 0.123% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9520 tsec 5.1040 #GCMRL# 427 dt 25.600000 rms 0.528 0.107% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9480 tsec 5.1010 #GCMRL# 428 dt 25.600000 rms 0.527 0.117% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.8670 tsec 5.0180 #GCMRL# 429 dt 25.600000 rms 0.526 0.112% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9480 tsec 5.1000 #GCMRL# 430 dt 25.600000 rms 0.526 0.115% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9500 tsec 5.1000 #GCMRL# 431 dt 25.600000 rms 0.525 0.101% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9470 tsec 5.1010 #GCMRL# 432 dt 25.600000 rms 0.525 0.098% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9620 tsec 5.1130 #GCMRL# 433 dt 25.600000 rms 0.524 0.086% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9520 tsec 5.1040 #GCMRL# 434 dt 25.600000 rms 0.524 0.091% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9580 tsec 5.1080 #GCMRL# 435 dt 25.600000 rms 0.523 0.080% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9680 tsec 5.1180 #GCMRL# 436 dt 25.600000 rms 0.523 0.099% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9670 tsec 5.1170 #GCMRL# 437 dt 25.600000 rms 0.522 0.081% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9700 tsec 5.1220 #GCMRL# 438 dt 25.600000 rms 0.522 0.088% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9670 tsec 5.1160 #GCMRL# 439 dt 25.600000 rms 0.522 0.020% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9700 tsec 5.6230 #GCMRL# 440 dt 25.600000 rms 0.522 -0.005% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.0380 tsec 6.2590 #FOTS# QuadFit found better minimum quadopt=(dt=2.8,rms=0.521822) vs oldopt=(dt=2,rms=0.521823) #GCMRL# 441 dt 2.800000 rms 0.522 0.000% neg 0 invalid 762 tFOTS 14.6950 tGradient 4.0300 tsec 19.8750 #GCMRL# 442 dt 2.000000 rms 0.522 0.001% neg 0 invalid 762 tFOTS 14.7020 tGradient 4.0270 tsec 19.8780 #FOTS# QuadFit found better minimum quadopt=(dt=1.6,rms=0.521796) vs oldopt=(dt=2,rms=0.521796) #GCMRL# 443 dt 1.600000 rms 0.522 0.004% neg 0 invalid 762 tFOTS 14.7060 tGradient 3.9490 tsec 19.8030 #FOTS# QuadFit found better minimum quadopt=(dt=1.6,rms=0.521797) vs oldopt=(dt=2,rms=0.521797) #GCAMreg# pass 0 level1 3 level2 1 tsec 889.277 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.12 tol=5.00e-02, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=16, sigma=0.5,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.522138 #FOTS# QuadFit found better minimum quadopt=(dt=25.6,rms=0.521311) vs oldopt=(dt=32,rms=0.521354) #GCMRL# 445 dt 25.600000 rms 0.521 0.158% neg 0 invalid 762 tFOTS 14.6910 tGradient 4.0270 tsec 19.8660 #GCMRL# 446 dt 32.000000 rms 0.521 0.054% neg 0 invalid 762 tFOTS 15.6160 tGradient 3.9530 tsec 20.7170 #GCMRL# 447 dt 8.000000 rms 0.521 0.000% neg 0 invalid 762 tFOTS 14.6980 tGradient 3.9640 tsec 20.8840 #GCMRL# 448 dt 8.000000 rms 0.521 0.004% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9480 tsec 5.0970 setting smoothness cost coefficient to 0.400 #GCAMreg# pass 0 level1 2 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.40 tol=5.00e-02, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=4, sigma=2.0,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.560055 #GCMRL# 450 dt 0.000000 rms 0.560 0.058% neg 0 invalid 762 tFOTS 13.7870 tGradient 3.5950 tsec 18.5300 #GCMRL# 451 dt 0.150000 rms 0.560 0.000% neg 0 invalid 762 tFOTS 13.7850 tGradient 3.5990 tsec 19.6060 #GCAMreg# pass 0 level1 2 level2 1 tsec 48.522 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.40 tol=5.00e-02, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=4, sigma=0.5,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.560055 #GCMRL# 453 dt 0.000000 rms 0.560 0.058% neg 0 invalid 762 tFOTS 13.7810 tGradient 3.5960 tsec 18.5320 #GCMRL# 454 dt 0.150000 rms 0.560 0.000% neg 0 invalid 762 tFOTS 13.7900 tGradient 3.5940 tsec 19.6130 setting smoothness cost coefficient to 1.000 #GCAMreg# pass 0 level1 1 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=1.00 tol=5.00e-02, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=1, sigma=2.0,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.634484 #FOTS# QuadFit found better minimum quadopt=(dt=1.79853,rms=0.626786) vs oldopt=(dt=1.28,rms=0.627571) #GCMRL# 456 dt 1.798535 rms 0.627 1.213% neg 0 invalid 762 tFOTS 13.7830 tGradient 3.4500 tsec 18.3810 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.626523) vs oldopt=(dt=0.32,rms=0.626557) #GCMRL# 457 dt 0.448000 rms 0.627 0.000% neg 0 invalid 762 tFOTS 13.7820 tGradient 3.3760 tsec 18.3440 #GCAMreg# pass 0 level1 1 level2 1 tsec 46.78 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=1.00 tol=5.00e-02, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=1, sigma=0.5,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.626823 #FOTS# QuadFit found better minimum quadopt=(dt=0.768,rms=0.625946) vs oldopt=(dt=1.28,rms=0.626146) #GCMRL# 459 dt 0.768000 rms 0.626 0.140% neg 0 invalid 762 tFOTS 14.6950 tGradient 3.2700 tsec 19.1150 #FOTS# QuadFit found better minimum quadopt=(dt=0.256,rms=0.62591) vs oldopt=(dt=0.32,rms=0.625915) #GCMRL# 460 dt 0.256000 rms 0.626 0.000% neg 0 invalid 762 tFOTS 14.6960 tGradient 3.3540 tsec 19.2360 resetting metric properties... setting smoothness cost coefficient to 2.000 #GCAMreg# pass 0 level1 0 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=2.00 tol=5.00e-02, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=0, sigma=2.0,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.541982 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.526404) vs oldopt=(dt=0.32,rms=0.530597) #GCMRL# 462 dt 0.448000 rms 0.526 2.874% neg 0 invalid 762 tFOTS 13.7960 tGradient 2.6980 tsec 17.6420 #FOTS# QuadFit found better minimum quadopt=(dt=0.384,rms=0.522396) vs oldopt=(dt=0.32,rms=0.523052) #GCMRL# 463 dt 0.384000 rms 0.522 0.761% neg 0 invalid 762 tFOTS 13.7890 tGradient 2.7010 tsec 17.6410 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.519408) vs oldopt=(dt=0.32,rms=0.520252) #GCMRL# 464 dt 0.448000 rms 0.519 0.572% neg 0 invalid 762 tFOTS 13.7880 tGradient 2.6990 tsec 17.6360 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.517485) vs oldopt=(dt=0.32,rms=0.518025) #GCMRL# 465 dt 0.448000 rms 0.517 0.370% neg 0 invalid 762 tFOTS 13.7920 tGradient 2.7830 tsec 17.7240 #GCMRL# 466 dt 0.320000 rms 0.516 0.196% neg 0 invalid 762 tFOTS 13.7980 tGradient 2.7840 tsec 17.7300 #FOTS# QuadFit found better minimum quadopt=(dt=0.384,rms=0.515467) vs oldopt=(dt=0.32,rms=0.51563) #GCMRL# 467 dt 0.384000 rms 0.515 0.194% neg 0 invalid 762 tFOTS 13.7830 tGradient 2.7820 tsec 17.7120 #FOTS# QuadFit found better minimum quadopt=(dt=0.384,rms=0.514644) vs oldopt=(dt=0.32,rms=0.514776) #GCMRL# 468 dt 0.384000 rms 0.515 0.160% neg 0 invalid 762 tFOTS 13.7830 tGradient 2.6180 tsec 17.5490 #FOTS# QuadFit found better minimum quadopt=(dt=0.416667,rms=0.513909) vs oldopt=(dt=0.32,rms=0.514068) #GCMRL# 469 dt 0.416667 rms 0.514 0.143% neg 0 invalid 762 tFOTS 13.7930 tGradient 2.6480 tsec 17.5900 #FOTS# QuadFit found better minimum quadopt=(dt=0.384,rms=0.513333) vs oldopt=(dt=0.32,rms=0.513422) #GCMRL# 470 dt 0.384000 rms 0.513 0.112% neg 0 invalid 762 tFOTS 13.7790 tGradient 2.6200 tsec 17.5470 #FOTS# QuadFit found better minimum quadopt=(dt=0.384,rms=0.512868) vs oldopt=(dt=0.32,rms=0.512938) #GCMRL# 471 dt 0.384000 rms 0.513 0.091% neg 0 invalid 762 tFOTS 13.7890 tGradient 2.6180 tsec 17.5550 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.512377) vs oldopt=(dt=0.32,rms=0.512501) #GCMRL# 472 dt 0.448000 rms 0.512 0.096% neg 0 invalid 762 tFOTS 13.7890 tGradient 2.6180 tsec 17.5550 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.511977) vs oldopt=(dt=0.32,rms=0.512072) #GCMRL# 473 dt 0.448000 rms 0.512 0.078% neg 0 invalid 762 tFOTS 13.7800 tGradient 2.6450 tsec 17.5730 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.511609) vs oldopt=(dt=0.32,rms=0.511692) #GCMRL# 474 dt 0.448000 rms 0.512 0.072% neg 0 invalid 762 tFOTS 13.7840 tGradient 2.6190 tsec 17.5510 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.511324) vs oldopt=(dt=0.32,rms=0.511385) #GCMRL# 475 dt 0.448000 rms 0.511 0.056% neg 0 invalid 762 tFOTS 13.7900 tGradient 2.6210 tsec 17.5590 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.511037) vs oldopt=(dt=0.32,rms=0.511093) #GCMRL# 476 dt 0.448000 rms 0.511 0.056% neg 0 invalid 762 tFOTS 13.7990 tGradient 2.6460 tsec 17.5930 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.510816) vs oldopt=(dt=0.32,rms=0.510854) #GCMRL# 477 dt 0.448000 rms 0.511 0.000% neg 0 invalid 762 tFOTS 13.7800 tGradient 2.6220 tsec 17.5900 #GCMRL# 478 dt 0.448000 rms 0.511 0.045% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6190 tsec 3.7730 #GCMRL# 479 dt 0.448000 rms 0.510 0.077% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6190 tsec 3.7660 #GCMRL# 480 dt 0.224000 rms 0.510 0.019% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6440 tsec 4.7640 #GCMRL# 481 dt 0.224000 rms 0.510 0.029% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6230 tsec 3.7700 #GCMRL# 482 dt 0.224000 rms 0.510 0.017% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.5940 tsec 4.2480 #GCMRL# 483 dt 0.224000 rms 0.510 0.025% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6180 tsec 3.7720 #GCMRL# 484 dt 0.224000 rms 0.510 0.013% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6200 tsec 4.2700 #GCMRL# 485 dt 0.224000 rms 0.510 0.021% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6460 tsec 3.7960 #GCMRL# 486 dt 0.224000 rms 0.509 0.013% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6210 tsec 4.3110 #FOTS# QuadFit found better minimum quadopt=(dt=0.384,rms=0.509398) vs oldopt=(dt=0.32,rms=0.509409) #GCMRL# 487 dt 0.384000 rms 0.509 0.020% neg 0 invalid 762 tFOTS 13.7820 tGradient 2.6190 tsec 17.5540 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.509308) vs oldopt=(dt=0.32,rms=0.509322) #GCMRL# 488 dt 0.448000 rms 0.509 0.000% neg 0 invalid 762 tFOTS 13.7790 tGradient 2.6190 tsec 17.5840 #GCMRL# 489 dt 0.448000 rms 0.509 0.014% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6200 tsec 3.7690 #GCMRL# 490 dt 0.448000 rms 0.509 0.034% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6220 tsec 3.7690 #GCMRL# 491 dt 0.448000 rms 0.509 0.037% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6460 tsec 3.7980 #GCMRL# 492 dt 0.448000 rms 0.509 0.051% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6200 tsec 3.7700 #GCMRL# 493 dt 0.448000 rms 0.509 0.011% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6290 tsec 4.2830 #GCMRL# 494 dt 0.448000 rms 0.509 0.005% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6220 tsec 4.3130 #GCMRL# 495 dt 0.320000 rms 0.508 0.011% neg 0 invalid 762 tFOTS 13.7920 tGradient 2.6430 tsec 17.5850 #FOTS# QuadFit found better minimum quadopt=(dt=0.448,rms=0.508427) vs oldopt=(dt=0.32,rms=0.508431) #GCMRL# 496 dt 0.448000 rms 0.508 0.000% neg 0 invalid 762 tFOTS 13.7830 tGradient 2.6220 tsec 17.5930 #GCMRL# 497 dt 0.224000 rms 0.508 0.006% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6240 tsec 4.7410 #GCMRL# 498 dt 0.224000 rms 0.508 0.005% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6220 tsec 3.7700 #GCMRL# 499 dt 0.224000 rms 0.508 0.006% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6460 tsec 4.3060 #GCAMreg# pass 0 level1 0 level2 1 tsec 433.426 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=2.00 tol=5.00e-02, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=0, sigma=0.5,type=2, relabel=0, neg=no blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.508672 #FOTS# QuadFit found better minimum quadopt=(dt=0.384,rms=0.505139) vs oldopt=(dt=0.32,rms=0.505624) #GCMRL# 501 dt 0.384000 rms 0.505 0.695% neg 0 invalid 762 tFOTS 13.7850 tGradient 2.6510 tsec 17.5870 #FOTS# QuadFit found better minimum quadopt=(dt=0.384,rms=0.504423) vs oldopt=(dt=0.32,rms=0.504526) #GCMRL# 502 dt 0.384000 rms 0.504 0.142% neg 0 invalid 762 tFOTS 13.7940 tGradient 2.6230 tsec 17.5650 #FOTS# QuadFit found better minimum quadopt=(dt=0.384,rms=0.504253) vs oldopt=(dt=0.32,rms=0.504265) #GCMRL# 503 dt 0.384000 rms 0.504 0.000% neg 0 invalid 762 tFOTS 13.7900 tGradient 2.6210 tsec 17.5990 #GCMRL# 504 dt 0.384000 rms 0.504 0.011% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6210 tsec 3.7700 #GCMRL# 505 dt 0.384000 rms 0.504 0.009% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.6450 tsec 3.8080 GCAMregister done in 74.2166 min ********************* ALLOWING NEGATIVE NODES IN DEFORMATION******************************** noneg post Starting GCAMregister() label assignment complete, 0 changed (0.00%) npasses = 1, nlevels = 6 #pass# 1 of 1 ************************ enabling zero nodes setting smoothness cost coefficient to 0.008 #GCAMreg# pass 0 level1 5 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.01 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=256, sigma=2.0,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.50177 #GCMRL# 507 dt 92.480000 rms 0.501 0.097% neg 0 invalid 762 tFOTS 16.5430 tGradient 6.1430 tsec 23.8350 #FOTS# QuadFit found better minimum quadopt=(dt=129.472,rms=0.501127) vs oldopt=(dt=92.48,rms=0.501156) #GCMRL# 508 dt 129.472000 rms 0.501 0.000% neg 0 invalid 762 tFOTS 16.5390 tGradient 6.1950 tsec 23.9200 #GCMRL# 509 dt 129.472000 rms 0.501 0.005% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.1510 tsec 7.3000 #GCMRL# 510 dt 129.472000 rms 0.501 0.026% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.1520 tsec 7.3050 #GCMRL# 511 dt 129.472000 rms 0.501 0.022% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.1420 tsec 7.2930 #GCAMreg# pass 0 level1 5 level2 1 tsec 81.537 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.01 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=256, sigma=0.5,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.501155 #FOTS# QuadFit found better minimum quadopt=(dt=221.952,rms=0.499667) vs oldopt=(dt=369.92,rms=0.500033) #GCMRL# 513 dt 221.952000 rms 0.500 0.297% neg 0 invalid 762 tFOTS 16.5720 tGradient 6.1510 tsec 23.8720 #FOTS# QuadFit found better minimum quadopt=(dt=73.984,rms=0.499272) vs oldopt=(dt=92.48,rms=0.499274) #GCMRL# 514 dt 73.984000 rms 0.499 0.000% neg 0 invalid 762 tFOTS 16.5310 tGradient 6.1280 tsec 23.8450 #GCMRL# 515 dt 73.984000 rms 0.499 0.022% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.1670 tsec 7.3180 #GCMRL# 516 dt 73.984000 rms 0.499 0.032% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.1520 tsec 7.3020 #GCMRL# 517 dt 73.984000 rms 0.499 0.046% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.1660 tsec 7.3180 #GCMRL# 518 dt 73.984000 rms 0.499 0.045% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.1450 tsec 7.2950 #GCMRL# 519 dt 73.984000 rms 0.498 0.041% neg 0 invalid 762 tFOTS 0.0000 tGradient 6.1690 tsec 7.3580 setting smoothness cost coefficient to 0.031 #GCAMreg# pass 0 level1 4 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.03 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=64, sigma=2.0,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.498738 #FOTS# QuadFit found better minimum quadopt=(dt=64,rms=0.497233) vs oldopt=(dt=103.68,rms=0.497602) iter 0, gcam->neg = 1 after 2 iterations, nbhd size=0, neg = 0 #GCMRL# 521 dt 64.000000 rms 0.497 0.302% neg 0 invalid 762 tFOTS 17.4680 tGradient 4.5990 tsec 25.0790 #FOTS# QuadFit found better minimum quadopt=(dt=124.416,rms=0.496126) vs oldopt=(dt=103.68,rms=0.496136) iter 0, gcam->neg = 2 after 0 iterations, nbhd size=0, neg = 0 #GCMRL# 522 dt 124.416000 rms 0.496 0.000% neg 0 invalid 762 tFOTS 16.5560 tGradient 4.6310 tsec 23.3010 iter 0, gcam->neg = 1 after 0 iterations, nbhd size=0, neg = 0 #GCAMreg# pass 0 level1 4 level2 1 tsec 60.775 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.03 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=64, sigma=0.5,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.496595 #FOTS# QuadFit found better minimum quadopt=(dt=65.3813,rms=0.493859) vs oldopt=(dt=103.68,rms=0.494424) #GCMRL# 524 dt 65.381295 rms 0.494 0.551% neg 0 invalid 762 tFOTS 17.4720 tGradient 4.6840 tsec 23.3050 #FOTS# QuadFit found better minimum quadopt=(dt=36.288,rms=0.493188) vs oldopt=(dt=25.92,rms=0.493257) #GCMRL# 525 dt 36.288000 rms 0.493 0.000% neg 0 invalid 762 tFOTS 17.4550 tGradient 4.6840 tsec 23.3260 #GCMRL# 526 dt 36.288000 rms 0.493 0.123% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.6060 tsec 5.7560 #GCMRL# 527 dt 36.288000 rms 0.492 0.148% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.5980 tsec 5.7490 #GCMRL# 528 dt 36.288000 rms 0.491 0.168% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.6030 tsec 5.7520 #GCMRL# 529 dt 36.288000 rms 0.490 0.171% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.6050 tsec 5.7550 #GCMRL# 530 dt 36.288000 rms 0.489 0.189% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.6040 tsec 5.7560 #GCMRL# 531 dt 36.288000 rms 0.488 0.190% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.6910 tsec 5.8400 #GCMRL# 532 dt 36.288000 rms 0.488 0.163% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.6010 tsec 5.7580 #GCMRL# 533 dt 36.288000 rms 0.487 0.144% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.6610 tsec 5.8130 iter 0, gcam->neg = 1 after 0 iterations, nbhd size=0, neg = 0 #GCMRL# 534 dt 36.288000 rms 0.486 0.135% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.6020 tsec 6.6710 iter 0, gcam->neg = 1 after 0 iterations, nbhd size=0, neg = 0 #GCMRL# 535 dt 36.288000 rms 0.486 0.137% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.6190 tsec 6.6900 #GCMRL# 536 dt 36.288000 rms 0.485 0.127% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.6880 tsec 5.8380 #GCMRL# 537 dt 36.288000 rms 0.484 0.107% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.6790 tsec 5.8310 #GCMRL# 538 dt 36.288000 rms 0.484 0.091% neg 0 invalid 762 tFOTS 0.0000 tGradient 4.6870 tsec 5.8750 #FOTS# QuadFit found better minimum quadopt=(dt=145.152,rms=0.483674) vs oldopt=(dt=103.68,rms=0.483724) #GCMRL# 539 dt 145.152000 rms 0.484 0.000% neg 0 invalid 762 tFOTS 16.5220 tGradient 4.6850 tsec 22.3930 setting smoothness cost coefficient to 0.118 #GCAMreg# pass 0 level1 3 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.12 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=16, sigma=2.0,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.484828 #FOTS# QuadFit found better minimum quadopt=(dt=55.1006,rms=0.481017) vs oldopt=(dt=32,rms=0.481457) iter 0, gcam->neg = 25 after 17 iterations, nbhd size=1, neg = 0 #GCMRL# 541 dt 55.100592 rms 0.481 0.768% neg 0 invalid 762 tFOTS 17.4730 tGradient 3.8440 tsec 31.3970 #FOTS# QuadFit found better minimum quadopt=(dt=44.8,rms=0.477911) vs oldopt=(dt=32,rms=0.478135) iter 0, gcam->neg = 8 after 6 iterations, nbhd size=0, neg = 0 #GCMRL# 542 dt 44.800000 rms 0.478 0.662% neg 0 invalid 762 tFOTS 17.4790 tGradient 4.0480 tsec 26.4160 #FOTS# QuadFit found better minimum quadopt=(dt=29.0233,rms=0.47624) vs oldopt=(dt=32,rms=0.47629) iter 0, gcam->neg = 13 after 4 iterations, nbhd size=0, neg = 0 #GCMRL# 543 dt 29.023256 rms 0.476 0.351% neg 0 invalid 762 tFOTS 17.4650 tGradient 3.8630 tsec 25.2850 #FOTS# QuadFit found better minimum quadopt=(dt=63.0154,rms=0.474364) vs oldopt=(dt=32,rms=0.474562) iter 0, gcam->neg = 21 after 15 iterations, nbhd size=1, neg = 0 #GCMRL# 544 dt 63.015385 rms 0.474 0.392% neg 0 invalid 762 tFOTS 17.4650 tGradient 3.8630 tsec 30.4650 #FOTS# QuadFit found better minimum quadopt=(dt=25.6,rms=0.473178) vs oldopt=(dt=32,rms=0.473262) iter 0, gcam->neg = 9 after 18 iterations, nbhd size=1, neg = 0 #GCMRL# 545 dt 25.600000 rms 0.473 0.000% neg 0 invalid 762 tFOTS 17.4700 tGradient 3.9500 tsec 32.0040 iter 0, gcam->neg = 7 after 8 iterations, nbhd size=1, neg = 0 #GCMRL# 546 dt 25.600000 rms 0.472 0.222% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9490 tsec 9.7810 iter 0, gcam->neg = 12 after 14 iterations, nbhd size=1, neg = 0 #GCMRL# 547 dt 25.600000 rms 0.471 0.243% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9620 tsec 12.6130 iter 0, gcam->neg = 35 after 12 iterations, nbhd size=0, neg = 0 #GCMRL# 548 dt 25.600000 rms 0.470 0.284% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.8730 tsec 11.5920 iter 0, gcam->neg = 40 after 11 iterations, nbhd size=0, neg = 0 #GCMRL# 549 dt 25.600000 rms 0.468 0.301% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9540 tsec 11.1880 iter 0, gcam->neg = 69 after 14 iterations, nbhd size=0, neg = 0 #GCMRL# 550 dt 25.600000 rms 0.467 0.291% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.8720 tsec 12.5290 iter 0, gcam->neg = 113 after 17 iterations, nbhd size=1, neg = 0 #GCMRL# 551 dt 25.600000 rms 0.466 0.254% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9640 tsec 14.0260 iter 0, gcam->neg = 134 after 27 iterations, nbhd size=1, neg = 0 #GCMRL# 552 dt 25.600000 rms 0.465 0.184% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.8710 tsec 18.6550 iter 0, gcam->neg = 138 after 29 iterations, nbhd size=1, neg = 0 #GCMRL# 553 dt 25.600000 rms 0.464 0.109% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9620 tsec 19.7000 iter 0, gcam->neg = 105 after 25 iterations, nbhd size=1, neg = 0 #GCMRL# 554 dt 25.600000 rms 0.464 0.109% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9230 tsec 17.7820 iter 0, gcam->neg = 135 after 26 iterations, nbhd size=1, neg = 0 #GCMRL# 555 dt 25.600000 rms 0.464 0.081% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9470 tsec 18.2990 #FOTS# QuadFit found better minimum quadopt=(dt=11.2,rms=0.463518) vs oldopt=(dt=8,rms=0.463524) iter 0, gcam->neg = 17 after 13 iterations, nbhd size=0, neg = 0 #GCMRL# 556 dt 11.200000 rms 0.464 0.000% neg 0 invalid 762 tFOTS 17.4670 tGradient 3.8630 tsec 29.5570 iter 0, gcam->neg = 11 after 7 iterations, nbhd size=0, neg = 0 #GCMRL# 557 dt 11.200000 rms 0.463 0.020% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9500 tsec 9.3070 iter 0, gcam->neg = 10 after 2 iterations, nbhd size=0, neg = 0 #GCMRL# 558 dt 11.200000 rms 0.463 0.016% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.8670 tsec 6.8770 iter 0, gcam->neg = 18 after 6 iterations, nbhd size=0, neg = 0 #GCMRL# 559 dt 11.200000 rms 0.463 0.026% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.8680 tsec 8.7570 iter 0, gcam->neg = 22 after 12 iterations, nbhd size=1, neg = 0 #GCMRL# 560 dt 11.200000 rms 0.463 0.037% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.8640 tsec 11.6230 iter 0, gcam->neg = 19 after 12 iterations, nbhd size=1, neg = 0 #GCMRL# 561 dt 11.200000 rms 0.463 0.041% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.8690 tsec 11.5950 iter 0, gcam->neg = 26 after 4 iterations, nbhd size=0, neg = 0 #GCAMreg# pass 0 level1 3 level2 1 tsec 381.855 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.12 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=16, sigma=0.5,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.46311 #FOTS# QuadFit found better minimum quadopt=(dt=44.8,rms=0.46039) vs oldopt=(dt=32,rms=0.460742) iter 0, gcam->neg = 9 after 11 iterations, nbhd size=0, neg = 0 #GCMRL# 563 dt 44.800000 rms 0.460 0.588% neg 0 invalid 762 tFOTS 17.4600 tGradient 3.8840 tsec 28.5910 #FOTS# QuadFit found better minimum quadopt=(dt=44.8,rms=0.459368) vs oldopt=(dt=32,rms=0.459506) iter 0, gcam->neg = 9 after 10 iterations, nbhd size=0, neg = 0 #GCMRL# 564 dt 44.800000 rms 0.459 0.000% neg 0 invalid 762 tFOTS 17.4570 tGradient 3.8700 tsec 28.1430 iter 0, gcam->neg = 16 after 17 iterations, nbhd size=1, neg = 0 setting smoothness cost coefficient to 0.400 #GCAMreg# pass 0 level1 2 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.40 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=4, sigma=2.0,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.467935 #FOTS# QuadFit found better minimum quadopt=(dt=1.728,rms=0.467529) vs oldopt=(dt=2.88,rms=0.467551) iter 0, gcam->neg = 1 after 2 iterations, nbhd size=0, neg = 0 #GCMRL# 566 dt 1.728000 rms 0.468 0.086% neg 0 invalid 762 tFOTS 17.5040 tGradient 3.4060 tsec 23.9190 #FOTS# QuadFit found better minimum quadopt=(dt=1.008,rms=0.467477) vs oldopt=(dt=0.72,rms=0.46748) iter 0, gcam->neg = 1 after 1 iterations, nbhd size=0, neg = 0 #GCMRL# 567 dt 1.008000 rms 0.467 0.000% neg 0 invalid 762 tFOTS 17.5040 tGradient 3.4090 tsec 23.4950 #GCMRL# 568 dt 1.008000 rms 0.467 0.004% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.4360 tsec 4.5850 iter 0, gcam->neg = 2 after 2 iterations, nbhd size=0, neg = 0 #GCAMreg# pass 0 level1 2 level2 1 tsec 64.059 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=0.40 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=4, sigma=0.5,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.467816 #FOTS# QuadFit found better minimum quadopt=(dt=4.84211,rms=0.467041) vs oldopt=(dt=2.88,rms=0.467107) iter 0, gcam->neg = 2 after 2 iterations, nbhd size=0, neg = 0 #GCMRL# 570 dt 4.842105 rms 0.467 0.165% neg 0 invalid 762 tFOTS 17.5030 tGradient 3.4130 tsec 23.9280 #FOTS# QuadFit found better minimum quadopt=(dt=4.61538,rms=0.466774) vs oldopt=(dt=2.88,rms=0.466817) #GCMRL# 571 dt 4.615385 rms 0.467 0.000% neg 0 invalid 762 tFOTS 17.4980 tGradient 3.4370 tsec 22.1220 iter 0, gcam->neg = 2 after 1 iterations, nbhd size=0, neg = 0 #GCMRL# 572 dt 4.615385 rms 0.467 0.041% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.4100 tsec 5.9560 iter 0, gcam->neg = 1 after 0 iterations, nbhd size=0, neg = 0 setting smoothness cost coefficient to 1.000 #GCAMreg# pass 0 level1 1 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=1.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=1, sigma=2.0,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.47653 #GCMRL# 574 dt 0.000050 rms 0.476 0.083% neg 0 invalid 762 tFOTS 22.0740 tGradient 3.4490 tsec 26.6730 #GCAMreg# pass 0 level1 1 level2 1 tsec 53.487 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=1.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=1, sigma=0.5,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.47653 #GCMRL# 576 dt 0.000000 rms 0.476 0.083% neg 0 invalid 762 tFOTS 16.6130 tGradient 3.4300 tsec 21.1950 resetting metric properties... setting smoothness cost coefficient to 2.000 #GCAMreg# pass 0 level1 0 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=2.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=0, sigma=2.0,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.460521 #FOTS# QuadFit found better minimum quadopt=(dt=1.49153,rms=0.438026) vs oldopt=(dt=1.28,rms=0.438508) iter 0, gcam->neg = 2070 after 16 iterations, nbhd size=1, neg = 0 #GCMRL# 578 dt 1.491525 rms 0.434 5.792% neg 0 invalid 762 tFOTS 17.5180 tGradient 2.7820 tsec 29.9690 #GCMRL# 579 dt 0.000013 rms 0.434 0.000% neg 0 invalid 762 tFOTS 22.0960 tGradient 2.5970 tsec 25.8820 #GCAMreg# pass 0 level1 0 level2 1 tsec 65.222 sigma 0.5 l_jacobian=1.00 l_label=1.00 l_log_likelihood=0.20 l_smoothness=2.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=0, sigma=0.5,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.434271 #GCMRL# 581 dt 0.000000 rms 0.434 0.105% neg 0 invalid 762 tFOTS 16.6220 tGradient 2.6130 tsec 20.3850 label assignment complete, 0 changed (0.00%) GCAMregister done in 20.0717 min Starting GCAMcomputeMaxPriorLabels() Morphing with label term set to 0 ******************************* Starting GCAMregister() label assignment complete, 0 changed (0.00%) npasses = 1, nlevels = 6 #pass# 1 of 1 ************************ enabling zero nodes setting smoothness cost coefficient to 0.008 #GCAMreg# pass 0 level1 5 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_log_likelihood=0.20 l_smoothness=0.01 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=256, sigma=2.0,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.424184 #GCAMreg# pass 0 level1 5 level2 1 tsec 28.227 sigma 0.5 l_jacobian=1.00 l_log_likelihood=0.20 l_smoothness=0.01 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=256, sigma=0.5,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.424184 #FOTS# QuadFit found better minimum quadopt=(dt=129.472,rms=0.424111) vs oldopt=(dt=92.48,rms=0.424116) iter 0, gcam->neg = 1 after 7 iterations, nbhd size=1, neg = 0 #GCMRL# 584 dt 129.472000 rms 0.424 0.017% neg 0 invalid 762 tFOTS 16.0480 tGradient 5.5140 tsec 26.9020 #GCMRL# 585 dt 92.480000 rms 0.424 0.000% neg 0 invalid 762 tFOTS 16.0360 tGradient 5.5120 tsec 22.7080 #GCMRL# 586 dt 92.480000 rms 0.424 0.003% neg 0 invalid 762 tFOTS 0.0000 tGradient 5.5100 tsec 6.6330 #GCMRL# 587 dt 92.480000 rms 0.424 0.003% neg 0 invalid 762 tFOTS 0.0000 tGradient 5.5210 tsec 6.6450 setting smoothness cost coefficient to 0.031 #GCAMreg# pass 0 level1 4 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_log_likelihood=0.20 l_smoothness=0.03 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=64, sigma=2.0,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.424183 #FOTS# QuadFit found better minimum quadopt=(dt=9.072,rms=0.42417) vs oldopt=(dt=6.48,rms=0.424171) iter 0, gcam->neg = 1 after 0 iterations, nbhd size=0, neg = 0 #GCMRL# 589 dt 9.072000 rms 0.424 0.003% neg 0 invalid 762 tFOTS 16.9700 tGradient 3.9650 tsec 22.9770 #FOTS# QuadFit found better minimum quadopt=(dt=0.972,rms=0.42417) vs oldopt=(dt=1.62,rms=0.42417) #GCMRL# 590 dt 0.972000 rms 0.424 0.000% neg 0 invalid 762 tFOTS 16.9660 tGradient 3.9700 tsec 22.1010 #GCAMreg# pass 0 level1 4 level2 1 tsec 55.704 sigma 0.5 l_jacobian=1.00 l_log_likelihood=0.20 l_smoothness=0.03 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=64, sigma=0.5,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.42417 #FOTS# QuadFit found better minimum quadopt=(dt=145.152,rms=0.423676) vs oldopt=(dt=103.68,rms=0.423775) iter 0, gcam->neg = 8 after 1 iterations, nbhd size=0, neg = 0 #GCMRL# 592 dt 145.152000 rms 0.424 0.117% neg 0 invalid 762 tFOTS 16.0510 tGradient 3.9680 tsec 22.5350 #FOTS# QuadFit found better minimum quadopt=(dt=124.416,rms=0.423482) vs oldopt=(dt=103.68,rms=0.423488) iter 0, gcam->neg = 14 after 9 iterations, nbhd size=1, neg = 0 #GCMRL# 593 dt 124.416000 rms 0.423 0.000% neg 0 invalid 762 tFOTS 16.0400 tGradient 3.9640 tsec 26.3200 iter 0, gcam->neg = 10 after 8 iterations, nbhd size=1, neg = 0 #GCMRL# 594 dt 124.416000 rms 0.423 0.017% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9830 tsec 9.7980 iter 0, gcam->neg = 12 after 3 iterations, nbhd size=0, neg = 0 #GCMRL# 595 dt 124.416000 rms 0.423 0.075% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9730 tsec 7.4310 iter 0, gcam->neg = 18 after 11 iterations, nbhd size=1, neg = 0 #GCMRL# 596 dt 124.416000 rms 0.423 0.060% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.9670 tsec 11.1940 iter 0, gcam->neg = 12 after 10 iterations, nbhd size=1, neg = 0 setting smoothness cost coefficient to 0.118 #GCAMreg# pass 0 level1 3 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_log_likelihood=0.20 l_smoothness=0.12 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=16, sigma=2.0,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.423348 #FOTS# QuadFit found better minimum quadopt=(dt=25.6,rms=0.422538) vs oldopt=(dt=32,rms=0.422616) iter 0, gcam->neg = 58 after 13 iterations, nbhd size=1, neg = 0 #GCMRL# 598 dt 25.600000 rms 0.423 0.147% neg 0 invalid 762 tFOTS 16.9770 tGradient 3.2330 tsec 28.4050 iter 0, gcam->neg = 59 after 23 iterations, nbhd size=1, neg = 0 #GCMRL# 599 dt 32.000000 rms 0.423 0.000% neg 0 invalid 762 tFOTS 16.9560 tGradient 3.2350 tsec 33.1290 iter 0, gcam->neg = 54 after 17 iterations, nbhd size=1, neg = 0 #GCMRL# 600 dt 32.000000 rms 0.422 0.063% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.2300 tsec 13.2760 iter 0, gcam->neg = 151 after 30 iterations, nbhd size=1, neg = 0 #GCAMreg# pass 0 level1 3 level2 1 tsec 99.721 sigma 0.5 l_jacobian=1.00 l_log_likelihood=0.20 l_smoothness=0.12 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=16, sigma=0.5,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.422373 #FOTS# QuadFit found better minimum quadopt=(dt=44.8,rms=0.420166) vs oldopt=(dt=32,rms=0.420438) iter 0, gcam->neg = 66 after 21 iterations, nbhd size=1, neg = 0 #GCMRL# 602 dt 44.800000 rms 0.420 0.533% neg 0 invalid 762 tFOTS 16.9510 tGradient 3.2360 tsec 32.1010 #FOTS# QuadFit found better minimum quadopt=(dt=44.8,rms=0.419202) vs oldopt=(dt=32,rms=0.419362) iter 0, gcam->neg = 51 after 21 iterations, nbhd size=1, neg = 0 #GCMRL# 603 dt 44.800000 rms 0.419 0.000% neg 0 invalid 762 tFOTS 16.9480 tGradient 3.2340 tsec 32.1540 iter 0, gcam->neg = 61 after 21 iterations, nbhd size=1, neg = 0 #GCMRL# 604 dt 44.800000 rms 0.419 0.059% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.2310 tsec 15.1470 iter 0, gcam->neg = 148 after 22 iterations, nbhd size=1, neg = 0 #GCMRL# 605 dt 44.800000 rms 0.418 0.111% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.2340 tsec 15.6580 iter 0, gcam->neg = 166 after 28 iterations, nbhd size=1, neg = 0 #GCMRL# 606 dt 44.800000 rms 0.418 0.056% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.2330 tsec 18.4710 iter 0, gcam->neg = 245 after 24 iterations, nbhd size=1, neg = 0 #GCMRL# 607 dt 44.800000 rms 0.418 0.058% neg 0 invalid 762 tFOTS 0.0000 tGradient 3.2320 tsec 16.5670 iter 0, gcam->neg = 277 after 24 iterations, nbhd size=1, neg = 0 setting smoothness cost coefficient to 0.400 #GCAMreg# pass 0 level1 2 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_log_likelihood=0.20 l_smoothness=0.40 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=4, sigma=2.0,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.421385 #FOTS# QuadFit found better minimum quadopt=(dt=8.29947,rms=0.420605) vs oldopt=(dt=11.52,rms=0.420723) iter 0, gcam->neg = 51 after 20 iterations, nbhd size=1, neg = 0 #GCMRL# 609 dt 8.299465 rms 0.421 0.180% neg 0 invalid 762 tFOTS 16.9810 tGradient 2.8020 tsec 31.2510 #FOTS# QuadFit found better minimum quadopt=(dt=9.216,rms=0.41994) vs oldopt=(dt=11.52,rms=0.419992) iter 0, gcam->neg = 88 after 21 iterations, nbhd size=1, neg = 0 #GCMRL# 610 dt 9.216000 rms 0.420 0.000% neg 0 invalid 762 tFOTS 16.9640 tGradient 2.7980 tsec 31.7370 iter 0, gcam->neg = 86 after 22 iterations, nbhd size=1, neg = 0 #GCMRL# 611 dt 9.216000 rms 0.420 0.084% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7980 tsec 15.2230 iter 0, gcam->neg = 103 after 24 iterations, nbhd size=1, neg = 0 #GCMRL# 612 dt 9.216000 rms 0.419 0.199% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.8030 tsec 16.1860 iter 0, gcam->neg = 203 after 21 iterations, nbhd size=1, neg = 0 #GCMRL# 613 dt 9.216000 rms 0.418 0.157% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.7980 tsec 14.7560 iter 0, gcam->neg = 354 after 37 iterations, nbhd size=2, neg = 0 #GCMRL# 614 dt 9.216000 rms 0.418 -0.042% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.8010 tsec 23.3540 #FOTS# QuadFit found better minimum quadopt=(dt=12.5217,rms=0.41736) vs oldopt=(dt=11.52,rms=0.417369) iter 0, gcam->neg = 140 after 22 iterations, nbhd size=1, neg = 0 #GCMRL# 615 dt 12.521739 rms 0.417 0.166% neg 0 invalid 762 tFOTS 16.9600 tGradient 2.8010 tsec 32.1830 #FOTS# QuadFit found better minimum quadopt=(dt=9.40659,rms=0.41712) vs oldopt=(dt=11.52,rms=0.417142) iter 0, gcam->neg = 91 after 20 iterations, nbhd size=1, neg = 0 #GCAMreg# pass 0 level1 2 level2 1 tsec 200.403 sigma 0.5 l_jacobian=1.00 l_log_likelihood=0.20 l_smoothness=0.40 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=4, sigma=0.5,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.417181 #FOTS# QuadFit found better minimum quadopt=(dt=14.0952,rms=0.415054) vs oldopt=(dt=11.52,rms=0.415139) iter 0, gcam->neg = 221 after 30 iterations, nbhd size=1, neg = 0 #GCMRL# 617 dt 14.095238 rms 0.415 0.552% neg 0 invalid 762 tFOTS 16.9780 tGradient 2.8230 tsec 35.9740 iter 0, gcam->neg = 88 after 19 iterations, nbhd size=1, neg = 0 #GCMRL# 618 dt 11.520000 rms 0.414 0.000% neg 0 invalid 762 tFOTS 16.9550 tGradient 2.7980 tsec 30.7790 iter 0, gcam->neg = 87 after 25 iterations, nbhd size=1, neg = 0 #GCMRL# 619 dt 11.520000 rms 0.414 0.060% neg 0 invalid 762 tFOTS 0.0000 tGradient 2.8000 tsec 16.6130 iter 0, gcam->neg = 197 after 25 iterations, nbhd size=1, neg = 0 setting smoothness cost coefficient to 1.000 #GCAMreg# pass 0 level1 1 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_log_likelihood=0.20 l_smoothness=1.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=1, sigma=2.0,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.419875 #GCMRL# 621 dt 0.000050 rms 0.420 0.000% neg 0 invalid 762 tFOTS 21.4310 tGradient 2.6330 tsec 25.1850 #GCAMreg# pass 0 level1 1 level2 1 tsec 50.574 sigma 0.5 l_jacobian=1.00 l_log_likelihood=0.20 l_smoothness=1.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=1, sigma=0.5,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.419875 resetting metric properties... setting smoothness cost coefficient to 2.000 #GCAMreg# pass 0 level1 0 level2 0 tsec 0 sigma 2 l_jacobian=1.00 l_log_likelihood=0.20 l_smoothness=2.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=0, sigma=2.0,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=2.000... GCAMRegisterLevel(): init RMS 0.410323 #FOTS# QuadFit found better minimum quadopt=(dt=0.885463,rms=0.401068) vs oldopt=(dt=1.28,rms=0.403108) iter 0, gcam->neg = 1065 after 20 iterations, nbhd size=1, neg = 0 #GCMRL# 624 dt 0.885463 rms 0.401 2.183% neg 0 invalid 762 tFOTS 17.0160 tGradient 1.9890 tsec 30.5260 #FOTS# QuadFit found better minimum quadopt=(dt=2.73438e-05,rms=0.401367) vs oldopt=(dt=1.95313e-05,rms=0.401367) #GCMRL# 625 dt 0.000027 rms 0.401 0.000% neg 0 invalid 762 tFOTS 21.4340 tGradient 1.9900 tsec 24.5840 #GCAMreg# pass 0 level1 0 level2 1 tsec 63.735 sigma 0.5 l_jacobian=1.00 l_log_likelihood=0.20 l_smoothness=2.00 tol=2.50e-01, dt=5.00e-02, exp_k=20.0, momentum=0.90, levels=6, niter=500, lbl_dist=10.00, avgs=0, sigma=0.5,type=2, relabel=0, neg=yes blurring input image with Gaussian with sigma=0.500... GCAMRegisterLevel(): init RMS 0.401367 #FOTS# QuadFit found better minimum quadopt=(dt=0.112,rms=0.40111) vs oldopt=(dt=0.08,rms=0.40114) #GCMRL# 627 dt 0.112000 rms 0.401 0.064% neg 0 invalid 762 tFOTS 17.0080 tGradient 1.9870 tsec 20.1210 #FOTS# QuadFit found better minimum quadopt=(dt=0.112,rms=0.40097) vs oldopt=(dt=0.08,rms=0.400989) #GCMRL# 628 dt 0.112000 rms 0.401 0.000% neg 0 invalid 762 tFOTS 17.0010 tGradient 1.9870 tsec 20.1530 #GCMRL# 629 dt 0.112000 rms 0.401 0.033% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9860 tsec 3.1090 #GCMRL# 630 dt 0.112000 rms 0.401 0.024% neg 0 invalid 762 tFOTS 0.0000 tGradient 1.9880 tsec 3.1190 GCAMregister done in 16.6045 min writing output transformation to transforms/talairach.m3z... GCAMwrite Calls to gcamLogLikelihoodEnergy 4467 tmin = 16.5382 Calls to gcamLabelEnergy 3913 tmin = 1.76193 Calls to gcamJacobianEnergy 4467 tmin = 13.1023 Calls to gcamSmoothnessEnergy 4467 tmin = 14.6771 Calls to gcamLogLikelihoodTerm 632 tmin = 4.87673 Calls to gcamLabelTerm 583 tmin = 8.26253 Calls to gcamJacobianTerm 632 tmin = 9.66112 Calls to gcamSmoothnessTerm 632 tmin = 3.33767 Calls to gcamComputeGradient 632 tmin = 50.9033 Calls to gcamComputeMetricProperties 7172 tmin = 21.4833 mri_ca_register took 2 hours, 14 minutes and 41 seconds. #VMPC# mri_ca_register VmPeak 2009500 FSRUNTIME@ mri_ca_register 2.2447 hours 1 threads @#@FSTIME 2026:03:01:13:59:27 mri_ca_register N 9 e 8080.88 S 2.23 U 8045.92 P 99% M 1336200 F 0 R 453151 W 0 c 2906 w 19 I 0 O 0 L 1.13 1.06 0.79 @#@FSLOADPOST 2026:03:01:16:14:08 mri_ca_register N 9 1.01 1.01 1.00 #-------------------------------------- #@# SubCort Seg Sun Mar 1 16:14:08 EST 2026 mri_ca_label -relabel_unlikely 9 .3 -prior 0.5 -align norm.mgz transforms/talairach.m3z /hpc/packages/minerva-centos7/freesurfer/7.2.0/freesurfer/average/RB_all_2020-01-02.gca aseg.auto_noCCseg.mgz sysname Linux hostname lh06c22 machine x86_64 setenv SUBJECTS_DIR /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer cd /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri mri_ca_label -relabel_unlikely 9 .3 -prior 0.5 -align norm.mgz transforms/talairach.m3z /hpc/packages/minerva-centos7/freesurfer/7.2.0/freesurfer/average/RB_all_2020-01-02.gca aseg.auto_noCCseg.mgz relabeling unlikely voxels with window_size = 9 and prior threshold 0.30 using Gibbs prior factor = 0.500 renormalizing sequences with structure alignment, equivalent to: -renormalize -renormalize_mean 0.500 -regularize 0.500 == Number of threads available to for OpenMP = 1 == reading 1 input volumes reading classifier array from /hpc/packages/minerva-centos7/freesurfer/7.2.0/freesurfer/average/RB_all_2020-01-02.gca reading input volume from norm.mgz average std[0] = 7.2 reading transform from transforms/talairach.m3z setting orig areas to linear transform determinant scaled 7.47 Atlas used for the 3D morph was /hpc/packages/minerva-centos7/freesurfer/7.2.0/freesurfer/average/RB_all_2020-01-02.gca average std = 7.2 using min determinant for regularization = 5.2 0 singular and 0 ill-conditioned covariance matrices regularized labeling volume... renormalizing by structure alignment.... renormalizing input #0 gca peak = 0.15521 (20) mri peak = 0.15992 (29) Left_Lateral_Ventricle (4): linear fit = 1.42 x + 0.0 (14807 voxels, overlap=0.130) Left_Lateral_Ventricle (4): linear fit = 1.42 x + 0.0 (14807 voxels, peak = 28), gca=28.5 gca peak = 0.20380 (13) mri peak = 0.17992 (28) Right_Lateral_Ventricle (43): linear fit = 2.08 x + 0.0 (8617 voxels, overlap=0.137) Right_Lateral_Ventricle (43): linear fit = 1.50 x + 0.0 (8617 voxels, peak = 27), gca=19.5 gca peak = 0.26283 (96) mri peak = 0.13582 (99) Right_Pallidum (52): linear fit = 1.03 x + 0.0 (639 voxels, overlap=0.782) Right_Pallidum (52): linear fit = 1.03 x + 0.0 (639 voxels, peak = 99), gca=99.4 gca peak = 0.15814 (97) mri peak = 0.10000 (100) Left_Pallidum (13): linear fit = 1.07 x + 0.0 (615 voxels, overlap=0.616) Left_Pallidum (13): linear fit = 1.07 x + 0.0 (615 voxels, peak = 103), gca=103.3 gca peak = 0.27624 (56) mri peak = 0.10825 (72) Right_Hippocampus (53): linear fit = 1.27 x + 0.0 (1191 voxels, overlap=0.019) Right_Hippocampus (53): linear fit = 1.27 x + 0.0 (1191 voxels, peak = 71), gca=71.4 gca peak = 0.28723 (59) mri peak = 0.10166 (77) Left_Hippocampus (17): linear fit = 1.29 x + 0.0 (918 voxels, overlap=0.018) Left_Hippocampus (17): linear fit = 1.29 x + 0.0 (918 voxels, peak = 76), gca=76.4 gca peak = 0.07623 (103) mri peak = 0.13324 (106) Right_Cerebral_White_Matter (41): linear fit = 1.01 x + 0.0 (30147 voxels, overlap=0.618) Right_Cerebral_White_Matter (41): linear fit = 1.01 x + 0.0 (30147 voxels, peak = 105), gca=104.5 gca peak = 0.07837 (105) mri peak = 0.11355 (106) Left_Cerebral_White_Matter (2): linear fit = 1.01 x + 0.0 (25011 voxels, overlap=0.568) Left_Cerebral_White_Matter (2): linear fit = 1.01 x + 0.0 (25011 voxels, peak = 107), gca=106.6 gca peak = 0.10165 (58) mri peak = 0.04408 (79) Left_Cerebral_Cortex (3): linear fit = 1.38 x + 0.0 (30660 voxels, overlap=0.000) Left_Cerebral_Cortex (3): linear fit = 1.38 x + 0.0 (30660 voxels, peak = 80), gca=80.3 gca peak = 0.11113 (58) mri peak = 0.04536 (77) Right_Cerebral_Cortex (42): linear fit = 1.32 x + 0.0 (31666 voxels, overlap=0.002) Right_Cerebral_Cortex (42): linear fit = 1.32 x + 0.0 (31666 voxels, peak = 76), gca=76.3 gca peak = 0.27796 (67) mri peak = 0.07906 (86) Right_Caudate (50): linear fit = 1.27 x + 0.0 (1144 voxels, overlap=0.023) Right_Caudate (50): linear fit = 1.27 x + 0.0 (1144 voxels, peak = 85), gca=85.4 gca peak = 0.14473 (69) mri peak = 0.10488 (88) Left_Caudate (11): linear fit = 1.16 x + 0.0 (1031 voxels, overlap=0.019) Left_Caudate (11): linear fit = 1.16 x + 0.0 (1031 voxels, peak = 80), gca=80.4 gca peak = 0.14301 (56) mri peak = 0.07317 (71) Left_Cerebellum_Cortex (8): linear fit = 1.25 x + 0.0 (29346 voxels, overlap=0.017) Left_Cerebellum_Cortex (8): linear fit = 1.25 x + 0.0 (29346 voxels, peak = 70), gca=69.7 gca peak = 0.14610 (55) mri peak = 0.06913 (68) Right_Cerebellum_Cortex (47): linear fit = 1.23 x + 0.0 (30000 voxels, overlap=0.018) Right_Cerebellum_Cortex (47): linear fit = 1.23 x + 0.0 (30000 voxels, peak = 67), gca=67.4 gca peak = 0.16309 (85) mri peak = 0.13479 (84) Left_Cerebellum_White_Matter (7): linear fit = 1.01 x + 0.0 (8005 voxels, overlap=0.854) Left_Cerebellum_White_Matter (7): linear fit = 1.01 x + 0.0 (8005 voxels, peak = 86), gca=86.3 gca peak = 0.15172 (84) mri peak = 0.13110 (85) Right_Cerebellum_White_Matter (46): linear fit = 1.01 x + 0.0 (8173 voxels, overlap=0.853) Right_Cerebellum_White_Matter (46): linear fit = 1.01 x + 0.0 (8173 voxels, peak = 85), gca=85.3 gca peak = 0.30461 (58) mri peak = 0.10937 (77) Left_Amygdala (18): linear fit = 1.33 x + 0.0 (336 voxels, overlap=0.053) Left_Amygdala (18): linear fit = 1.33 x + 0.0 (336 voxels, peak = 77), gca=76.9 gca peak = 0.32293 (57) mri peak = 0.14339 (72) Right_Amygdala (54): linear fit = 1.27 x + 0.0 (537 voxels, overlap=0.043) Right_Amygdala (54): linear fit = 1.27 x + 0.0 (537 voxels, peak = 73), gca=72.7 gca peak = 0.11083 (90) mri peak = 0.10282 (94) Left_Thalamus (10): linear fit = 1.07 x + 0.0 (4103 voxels, overlap=0.630) Left_Thalamus (10): linear fit = 1.07 x + 0.0 (4103 voxels, peak = 96), gca=95.9 gca peak = 0.11393 (83) mri peak = 0.11176 (90) Right_Thalamus (49): linear fit = 1.10 x + 0.0 (4077 voxels, overlap=0.519) Right_Thalamus (49): linear fit = 1.10 x + 0.0 (4077 voxels, peak = 91), gca=90.9 gca peak = 0.08575 (81) mri peak = 0.09901 (91) Left_Putamen (12): linear fit = 1.12 x + 0.0 (1434 voxels, overlap=0.075) Left_Putamen (12): linear fit = 1.12 x + 0.0 (1434 voxels, peak = 91), gca=91.1 gca peak = 0.08618 (78) mri peak = 0.10058 (88) Right_Putamen (51): linear fit = 1.12 x + 0.0 (1536 voxels, overlap=0.176) Right_Putamen (51): linear fit = 1.12 x + 0.0 (1536 voxels, peak = 88), gca=87.8 gca peak = 0.08005 (78) mri peak = 0.11898 (84) Brain_Stem (16): linear fit = 1.07 x + 0.0 (15912 voxels, overlap=0.429) Brain_Stem (16): linear fit = 1.07 x + 0.0 (15912 voxels, peak = 83), gca=83.1 gca peak = 0.12854 (88) mri peak = 0.09446 (95) Right_VentralDC (60): linear fit = 1.09 x + 0.0 (1729 voxels, overlap=0.420) Right_VentralDC (60): linear fit = 1.09 x + 0.0 (1729 voxels, peak = 95), gca=95.5 gca peak = 0.15703 (87) mri peak = 0.09319 (96) Left_VentralDC (28): linear fit = 1.08 x + 0.0 (1738 voxels, overlap=0.329) Left_VentralDC (28): linear fit = 1.08 x + 0.0 (1738 voxels, peak = 94), gca=93.5 gca peak = 0.17522 (25) mri peak = 0.23844 (31) Third_Ventricle (14): linear fit = 1.16 x + 0.0 (296 voxels, overlap=0.582) Third_Ventricle (14): linear fit = 1.16 x + 0.0 (296 voxels, peak = 29), gca=29.1 gca peak = 0.17113 (14) mri peak = 0.14697 (26) Fourth_Ventricle (15): linear fit = 1.77 x + 0.0 (291 voxels, overlap=0.177) Fourth_Ventricle (15): linear fit = 1.77 x + 0.0 (291 voxels, peak = 25), gca=24.9 gca peak Unknown = 0.94777 ( 0) gca peak Left_Inf_Lat_Vent = 0.16627 (28) gca peak Fourth_Ventricle = 0.17113 (14) gca peak CSF = 0.20346 (36) gca peak Left_Accumbens_area = 0.70646 (62) gca peak Left_undetermined = 1.00000 (28) gca peak Left_vessel = 0.89917 (53) gca peak Left_choroid_plexus = 0.11689 (35) gca peak Right_Inf_Lat_Vent = 0.25504 (23) gca peak Right_Accumbens_area = 0.31650 (65) gca peak Right_vessel = 0.77268 (52) gca peak Right_choroid_plexus = 0.13275 (38) gca peak Fifth_Ventricle = 0.60973 (33) gca peak WM_hypointensities = 0.11013 (77) gca peak non_WM_hypointensities = 0.11354 (41) gca peak Optic_Chiasm = 0.51646 (76) not using caudate to estimate GM means estimating mean gm scale to be 1.31 x + 0.0 estimating mean wm scale to be 1.01 x + 0.0 estimating mean csf scale to be 1.36 x + 0.0 Left_Pallidum too bright - rescaling by 0.991 (from 1.065) to 102.4 (was 103.3) saving intensity scales to aseg.auto_noCCseg.label_intensities.txt renormalizing by structure alignment.... renormalizing input #0 gca peak = 0.11872 (26) mri peak = 0.15992 (29) Left_Lateral_Ventricle (4): linear fit = 0.94 x + 0.0 (14807 voxels, overlap=0.689) Left_Lateral_Ventricle (4): linear fit = 0.94 x + 0.0 (14807 voxels, peak = 25), gca=24.6 gca peak = 0.16931 (19) mri peak = 0.17992 (28) Right_Lateral_Ventricle (43): linear fit = 1.39 x + 0.0 (8617 voxels, overlap=0.257) Right_Lateral_Ventricle (43): linear fit = 1.39 x + 0.0 (8617 voxels, peak = 27), gca=26.5 gca peak = 0.20897 (99) mri peak = 0.13582 (99) Right_Pallidum (52): linear fit = 1.00 x + 0.0 (639 voxels, overlap=1.004) Right_Pallidum (52): linear fit = 1.00 x + 0.0 (639 voxels, peak = 99), gca=99.5 gca peak = 0.17574 (100) mri peak = 0.10000 (100) Left_Pallidum (13): linear fit = 1.00 x + 0.0 (615 voxels, overlap=0.999) Left_Pallidum (13): linear fit = 1.00 x + 0.0 (615 voxels, peak = 100), gca=100.5 gca peak = 0.26583 (71) mri peak = 0.10825 (72) Right_Hippocampus (53): linear fit = 1.00 x + 0.0 (1191 voxels, overlap=0.963) Right_Hippocampus (53): linear fit = 1.00 x + 0.0 (1191 voxels, peak = 71), gca=71.0 gca peak = 0.28793 (73) mri peak = 0.10166 (77) Left_Hippocampus (17): linear fit = 1.01 x + 0.0 (918 voxels, overlap=1.000) Left_Hippocampus (17): linear fit = 1.01 x + 0.0 (918 voxels, peak = 74), gca=74.1 gca peak = 0.07895 (105) mri peak = 0.13324 (106) Right_Cerebral_White_Matter (41): linear fit = 1.00 x + 0.0 (30147 voxels, overlap=0.677) Right_Cerebral_White_Matter (41): linear fit = 1.00 x + 0.0 (30147 voxels, peak = 106), gca=105.5 gca peak = 0.07852 (106) mri peak = 0.11355 (106) Left_Cerebral_White_Matter (2): linear fit = 1.00 x + 0.0 (25011 voxels, overlap=0.637) Left_Cerebral_White_Matter (2): linear fit = 1.00 x + 0.0 (25011 voxels, peak = 106), gca=106.0 gca peak = 0.06920 (80) mri peak = 0.04408 (79) Left_Cerebral_Cortex (3): linear fit = 1.00 x + 0.0 (30660 voxels, overlap=0.883) Left_Cerebral_Cortex (3): linear fit = 1.00 x + 0.0 (30660 voxels, peak = 80), gca=80.0 gca peak = 0.08672 (77) mri peak = 0.04536 (77) Right_Cerebral_Cortex (42): linear fit = 1.00 x + 0.0 (31666 voxels, overlap=0.899) Right_Cerebral_Cortex (42): linear fit = 1.00 x + 0.0 (31666 voxels, peak = 77), gca=77.0 gca peak = 0.19861 (85) mri peak = 0.07906 (86) Right_Caudate (50): linear fit = 0.99 x + 0.0 (1144 voxels, overlap=0.997) Right_Caudate (50): linear fit = 0.99 x + 0.0 (1144 voxels, peak = 84), gca=83.7 gca peak = 0.11605 (81) mri peak = 0.10488 (88) Left_Caudate (11): linear fit = 1.00 x + 0.0 (1031 voxels, overlap=0.933) Left_Caudate (11): linear fit = 1.00 x + 0.0 (1031 voxels, peak = 81), gca=81.0 gca peak = 0.11273 (69) mri peak = 0.07317 (71) Left_Cerebellum_Cortex (8): linear fit = 1.00 x + 0.0 (29346 voxels, overlap=0.943) Left_Cerebellum_Cortex (8): linear fit = 1.00 x + 0.0 (29346 voxels, peak = 69), gca=69.0 gca peak = 0.12972 (68) mri peak = 0.06913 (68) Right_Cerebellum_Cortex (47): linear fit = 0.99 x + 0.0 (30000 voxels, overlap=0.951) Right_Cerebellum_Cortex (47): linear fit = 0.99 x + 0.0 (30000 voxels, peak = 67), gca=67.0 gca peak = 0.15848 (86) mri peak = 0.13479 (84) Left_Cerebellum_White_Matter (7): linear fit = 1.00 x + 0.0 (8005 voxels, overlap=0.913) Left_Cerebellum_White_Matter (7): linear fit = 1.00 x + 0.0 (8005 voxels, peak = 86), gca=86.0 gca peak = 0.15994 (85) mri peak = 0.13110 (85) Right_Cerebellum_White_Matter (46): linear fit = 1.00 x + 0.0 (8173 voxels, overlap=0.916) Right_Cerebellum_White_Matter (46): linear fit = 1.00 x + 0.0 (8173 voxels, peak = 85), gca=85.0 gca peak = 0.28231 (77) mri peak = 0.10937 (77) Left_Amygdala (18): linear fit = 1.00 x + 0.0 (336 voxels, overlap=1.000) Left_Amygdala (18): linear fit = 1.00 x + 0.0 (336 voxels, peak = 77), gca=77.0 gca peak = 0.22498 (73) mri peak = 0.14339 (72) Right_Amygdala (54): linear fit = 1.00 x + 0.0 (537 voxels, overlap=1.000) Right_Amygdala (54): linear fit = 1.00 x + 0.0 (537 voxels, peak = 73), gca=73.0 gca peak = 0.11065 (94) mri peak = 0.10282 (94) Left_Thalamus (10): linear fit = 1.00 x + 0.0 (4103 voxels, overlap=0.885) Left_Thalamus (10): linear fit = 1.00 x + 0.0 (4103 voxels, peak = 94), gca=93.5 gca peak = 0.10377 (91) mri peak = 0.11176 (90) Right_Thalamus (49): linear fit = 1.00 x + 0.0 (4077 voxels, overlap=0.891) Right_Thalamus (49): linear fit = 1.00 x + 0.0 (4077 voxels, peak = 91), gca=90.5 gca peak = 0.08104 (91) mri peak = 0.09901 (91) Left_Putamen (12): linear fit = 1.02 x + 0.0 (1434 voxels, overlap=0.734) Left_Putamen (12): linear fit = 1.02 x + 0.0 (1434 voxels, peak = 93), gca=93.3 gca peak = 0.09539 (87) mri peak = 0.10058 (88) Right_Putamen (51): linear fit = 1.01 x + 0.0 (1536 voxels, overlap=0.820) Right_Putamen (51): linear fit = 1.01 x + 0.0 (1536 voxels, peak = 88), gca=88.3 gca peak = 0.07251 (86) mri peak = 0.11898 (84) Brain_Stem (16): linear fit = 0.99 x + 0.0 (15912 voxels, overlap=0.677) Brain_Stem (16): linear fit = 0.99 x + 0.0 (15912 voxels, peak = 85), gca=84.7 gca peak = 0.11740 (97) mri peak = 0.09446 (95) Right_VentralDC (60): linear fit = 1.01 x + 0.0 (1729 voxels, overlap=0.800) Right_VentralDC (60): linear fit = 1.01 x + 0.0 (1729 voxels, peak = 98), gca=98.5 gca peak = 0.14484 (93) mri peak = 0.09319 (96) Left_VentralDC (28): linear fit = 1.01 x + 0.0 (1738 voxels, overlap=0.861) Left_VentralDC (28): linear fit = 1.01 x + 0.0 (1738 voxels, peak = 94), gca=94.4 gca peak = 0.17308 (29) mri peak = 0.23844 (31) Third_Ventricle (14): linear fit = 1.04 x + 0.0 (296 voxels, overlap=0.844) Third_Ventricle (14): linear fit = 1.04 x + 0.0 (296 voxels, peak = 30), gca=30.3 gca peak = 0.15151 (20) mri peak = 0.14697 (26) Fourth_Ventricle (15): linear fit = 1.29 x + 0.0 (291 voxels, overlap=0.291) Fourth_Ventricle (15): linear fit = 1.29 x + 0.0 (291 voxels, peak = 26), gca=25.9 gca peak Unknown = 0.94777 ( 0) gca peak Left_Inf_Lat_Vent = 0.14083 (36) gca peak CSF = 0.17302 (49) gca peak Left_Accumbens_area = 0.54230 (73) gca peak Left_undetermined = 0.99358 (33) gca peak Left_vessel = 0.63642 (53) gca peak Left_choroid_plexus = 0.11374 (35) gca peak Right_Inf_Lat_Vent = 0.17464 (37) gca peak Right_Accumbens_area = 0.36006 (82) gca peak Right_vessel = 0.77268 (52) gca peak Right_choroid_plexus = 0.13297 (38) gca peak Fifth_Ventricle = 0.59466 (43) gca peak WM_hypointensities = 0.09617 (77) gca peak non_WM_hypointensities = 0.14069 (41) gca peak Optic_Chiasm = 0.51647 (76) not using caudate to estimate GM means estimating mean gm scale to be 1.00 x + 0.0 estimating mean wm scale to be 1.00 x + 0.0 estimating mean csf scale to be 1.17 x + 0.0 saving intensity scales to aseg.auto_noCCseg.label_intensities.txt saving sequentially combined intensity scales to aseg.auto_noCCseg.label_intensities.txt 54875 voxels changed in iteration 0 of unlikely voxel relabeling 193 voxels changed in iteration 1 of unlikely voxel relabeling 5 voxels changed in iteration 2 of unlikely voxel relabeling 0 voxels changed in iteration 3 of unlikely voxel relabeling 62203 gm and wm labels changed (%28 to gray, %72 to white out of all changed labels) 472 hippocampal voxels changed. 0 amygdala voxels changed. Reclassifying using Gibbs Priors pass 1: 78575 changed. image ll: -2.138, PF=0.500 pass 2: 20644 changed. image ll: -2.137, PF=0.500 pass 3: 6370 changed. pass 4: 2438 changed. 50200 voxels changed in iteration 0 of unlikely voxel relabeling 280 voxels changed in iteration 1 of unlikely voxel relabeling 25 voxels changed in iteration 2 of unlikely voxel relabeling 0 voxels changed in iteration 3 of unlikely voxel relabeling 7350 voxels changed in iteration 0 of unlikely voxel relabeling 101 voxels changed in iteration 1 of unlikely voxel relabeling 4 voxels changed in iteration 2 of unlikely voxel relabeling 2 voxels changed in iteration 3 of unlikely voxel relabeling 0 voxels changed in iteration 4 of unlikely voxel relabeling 5434 voxels changed in iteration 0 of unlikely voxel relabeling 27 voxels changed in iteration 1 of unlikely voxel relabeling 5 voxels changed in iteration 2 of unlikely voxel relabeling 0 voxels changed in iteration 3 of unlikely voxel relabeling 5462 voxels changed in iteration 0 of unlikely voxel relabeling 23 voxels changed in iteration 1 of unlikely voxel relabeling 0 voxels changed in iteration 2 of unlikely voxel relabeling !!!!!!!!! ventricle segment 1 with volume 32936 above threshold 100 - not erasing !!!!!!!!!! !!!!!!!!! ventricle segment 2 with volume 1335 above threshold 100 - not erasing !!!!!!!!!! !!!!!!!!! ventricle segment 3 with volume 23477 above threshold 100 - not erasing !!!!!!!!!! !!!!!!!!! ventricle segment 0 with volume 1162 above threshold 100 - not erasing !!!!!!!!!! writing labeled volume to aseg.auto_noCCseg.mgz mri_ca_label utimesec 2330.541257 mri_ca_label stimesec 1.415061 mri_ca_label ru_maxrss 2109736 mri_ca_label ru_ixrss 0 mri_ca_label ru_idrss 0 mri_ca_label ru_isrss 0 mri_ca_label ru_minflt 413361 mri_ca_label ru_majflt 0 mri_ca_label ru_nswap 0 mri_ca_label ru_inblock 0 mri_ca_label ru_oublock 0 mri_ca_label ru_msgsnd 0 mri_ca_label ru_msgrcv 0 mri_ca_label ru_nsignals 0 mri_ca_label ru_nvcsw 30 mri_ca_label ru_nivcsw 897 auto-labeling took 39 minutes and 1 seconds. @#@FSTIME 2026:03:01:16:14:08 mri_ca_label N 10 e 2340.76 S 1.52 U 2330.54 P 99% M 2109736 F 0 R 413367 W 0 c 897 w 31 I 0 O 0 L 1.01 1.01 1.00 @#@FSLOADPOST 2026:03:01:16:53:09 mri_ca_label N 10 1.11 1.20 1.18 #-------------------------------------- #@# CC Seg Sun Mar 1 16:53:09 EST 2026 mri_cc -aseg aseg.auto_noCCseg.mgz -o aseg.auto.mgz -lta /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/transforms/cc_up.lta sub-02 will read input aseg from aseg.auto_noCCseg.mgz writing aseg with cc labels to aseg.auto.mgz will write lta as /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/transforms/cc_up.lta reading aseg from /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/aseg.auto_noCCseg.mgz reading norm from /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/norm.mgz MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab 19610 voxels in left wm, 35713 in right wm, xrange [123, 132] searching rotation angles z=[-11 3], y=[-7 7] searching scale 1 Z rot -11.0 searching scale 1 Z rot -10.8 searching scale 1 Z rot -10.5 searching scale 1 Z rot -10.3 searching scale 1 Z rot -10.0 searching scale 1 Z rot -9.8 searching scale 1 Z rot -9.5 searching scale 1 Z rot -9.3 searching scale 1 Z rot -9.0 searching scale 1 Z rot -8.8 searching scale 1 Z rot -8.5 searching scale 1 Z rot -8.3 searching scale 1 Z rot -8.0 searching scale 1 Z rot -7.8 searching scale 1 Z rot -7.5 searching scale 1 Z rot -7.3 searching scale 1 Z rot -7.0 searching scale 1 Z rot -6.8 searching scale 1 Z rot -6.5 searching scale 1 Z rot -6.3 searching scale 1 Z rot -6.0 searching scale 1 Z rot -5.8 searching scale 1 Z rot -5.5 searching scale 1 Z rot -5.3 searching scale 1 Z rot -5.0 searching scale 1 Z rot -4.8 searching scale 1 Z rot -4.5 searching scale 1 Z rot -4.3 searching scale 1 Z rot -4.0 searching scale 1 Z rot -3.8 searching scale 1 Z rot -3.5 searching scale 1 Z rot -3.3 searching scale 1 Z rot -3.0 searching scale 1 Z rot -2.8 searching scale 1 Z rot -2.5 searching scale 1 Z rot -2.3 searching scale 1 Z rot -2.0 searching scale 1 Z rot -1.8 searching scale 1 Z rot -1.5 searching scale 1 Z rot -1.3 searching scale 1 Z rot -1.0 searching scale 1 Z rot -0.8 searching scale 1 Z rot -0.5 searching scale 1 Z rot -0.3 searching scale 1 Z rot -0.0 searching scale 1 Z rot 0.2 searching scale 1 Z rot 0.5 searching scale 1 Z rot 0.7 searching scale 1 Z rot 1.0 searching scale 1 Z rot 1.2 searching scale 1 Z rot 1.5 searching scale 1 Z rot 1.7 searching scale 1 Z rot 2.0 searching scale 1 Z rot 2.2 searching scale 1 Z rot 2.5 searching scale 1 Z rot 2.7 searching scale 1 Z rot 3.0 global minimum found at slice 128.0, rotations (0.47, -4.04) final transformation (x=128.0, yr=0.469, zr=-4.036): 0.99749 0.07038 0.00816 -8.76962; -0.07037 0.99752 -0.00058 20.35838; -0.00819 -0.00000 0.99997 24.05120; 0.00000 0.00000 0.00000 1.00000; updating x range to be [126, 132] in xformed coordinates best xformed slice 128 min_x_fornix = 143 min_x_fornix = 147 min_x_fornix = 152 min_x_fornix = 151 min_x_fornix = 145 cc center is found at 128 117 105 eigenvectors: 0.00041 -0.00175 1.00000; -0.17774 -0.98408 -0.00165; 0.98408 -0.17774 -0.00071; MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab error in mid anterior detected - correcting... writing aseg with callosum to /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri/aseg.auto.mgz... corpus callosum segmentation took 0.7 minutes #VMPC# mri_cc VmPeak 429524 mri_cc done @#@FSTIME 2026:03:01:16:53:09 mri_cc N 7 e 39.72 S 0.15 U 39.43 P 99% M 343492 F 0 R 13252 W 0 c 32 w 18 I 0 O 0 L 1.11 1.20 1.18 @#@FSLOADPOST 2026:03:01:16:53:48 mri_cc N 7 1.27 1.24 1.19 #-------------------------------------- #@# Merge ASeg Sun Mar 1 16:53:49 EST 2026 cp aseg.auto.mgz aseg.presurf.mgz #-------------------------------------------- #@# Intensity Normalization2 Sun Mar 1 16:53:49 EST 2026 /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri mri_normalize -seed 1234 -mprage -aseg aseg.presurf.mgz -mask brainmask.mgz norm.mgz brain.mgz setting seed for random number genererator to 1234 assuming input volume is MGH (Van der Kouwe) MP-RAGE using segmentation for initial intensity normalization using MR volume brainmask.mgz to mask input volume... reading mri_src from norm.mgz... Reading aseg aseg.presurf.mgz normalizing image... NOT doing gentle normalization with control points/label processing with aseg MRIcopyHeader(): source has ctab removing outliers in the aseg WM... MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab 600 control points removed MRIcopyHeader(): source has ctab Building bias image building Voronoi diagram... performing soap bubble smoothing, sigma = 0... Smoothing with sigma 8 Applying bias correction building Voronoi diagram... performing soap bubble smoothing, sigma = 8... Iterating 2 times --------------------------------- 3d normalization pass 1 of 2 white matter peak found at 110 white matter peak found at 109 gm peak at 82 (82), valley at 54 (54) csf peak at 29, setting threshold to 64 building Voronoi diagram... performing soap bubble smoothing, sigma = 8... --------------------------------- 3d normalization pass 2 of 2 white matter peak found at 110 white matter peak found at 110 gm peak at 83 (83), valley at 62 (62) csf peak at 29, setting threshold to 65 building Voronoi diagram... performing soap bubble smoothing, sigma = 8... Done iterating --------------------------------- writing output to brain.mgz 3D bias adjustment took 2 minutes and 13 seconds. @#@FSTIME 2026:03:01:16:53:49 mri_normalize N 9 e 133.93 S 0.74 U 132.68 P 99% M 1240772 F 0 R 219197 W 0 c 203 w 17 I 0 O 0 L 1.27 1.24 1.19 @#@FSLOADPOST 2026:03:01:16:56:03 mri_normalize N 9 1.22 1.23 1.18 #-------------------------------------------- #@# Mask BFS Sun Mar 1 16:56:03 EST 2026 /sc/arion/projects/ConAD/testing/dopamine_longitudinal_fs/orig_data/both_tps/freesurfer/sub-02/mri mri_mask -T 5 brain.mgz brainmask.mgz brain.finalsurfs.mgz threshold mask volume at 5 DoAbs = 0 Found 1786873 voxels in mask (pct= 10.65) Writing masked volume to brain.finalsurfs.mgz...done. @#@FSTIME 2026:03:01:16:56:03 mri_mask N 5 e 0.87 S 0.02 U 0.83 P 99% M 73448 F 0 R 2952 W 0 c 4 w 13 I 0 O 0 L 1.22 1.23 1.18 @#@FSLOADPOST 2026:03:01:16:56:03 mri_mask N 5 1.22 1.23 1.18 #-------------------------------------------- #@# WM Segmentation Sun Mar 1 16:56:03 EST 2026 AntsDenoiseImageFs -i brain.mgz -o antsdn.brain.mgz @#@FSTIME 2026:03:01:16:56:04 AntsDenoiseImageFs N 4 e 49.85 S 0.06 U 49.62 P 99% M 350852 F 0 R 3996 W 0 c 24 w 7 I 0 O 0 L 1.22 1.23 1.18 @#@FSLOADPOST 2026:03:01:16:56:53 AntsDenoiseImageFs N 4 1.10 1.19 1.17 mri_segment -wsizemm 13 -mprage antsdn.brain.mgz wm.seg.mgz wsizemm = 13, voxres = 1, wsize = 13 Widening wm low from 89 to 79 assuming input volume is MGH (Van der Kouwe) MP-RAGE wm mean: 110 wsize: 13 wm low: 79 wm hi: 125 gray low: 30 gray hi: 99 Doing initial trinary intensity segmentation Using local statistics to label ambiguous voxels Autodetecting stats Computing class statistics for intensity windows... CCS WM (101.0): 101.3 +- 5.4 [79.0 --> 125.0] CCS GM (75.0) : 73.5 +- 11.7 [30.0 --> 95.0] white_mean 101.271 white_sigma 5.40032 gray_mean 73.5384 gray_sigma 11.7361 setting bottom of white matter range wm_low to 85.3 setting top of gray matter range gray_hi to 97.0 wm_low 85.2745 wm_hi 125 gray_low 30 gray_hi 97.0106 Redoing initial intensity segmentation... Recomputing local statistics to label ambiguous voxels... wm_low 85.2745 wm_hi 125 gray_low 30 gray_hi 97.0106 using local geometry to label remaining ambiguous voxels... polvwsize = 5, polvlen = 3, gray_hi = 97.0106, wm_low = 85.2745 MRIcpolvMedianCurveSegment(): wsize=5, len=3, gmhi=97.0106, wmlow=85.2745 240437 voxels processed (1.43%) 125585 voxels white (0.75%) 114852 voxels non-white (0.68%) Reclassifying voxels using Gaussian border classifier niter=1 MRIreclassify(): wm_low=80.2745, gray_hi=97.0106, wsize=13 375688 voxels tested (2.24%) 69637 voxels changed (0.42%) 70355 multi-scale searches (0.42%) Recovering bright white MRIrecoverBrightWhite() wm_low 85.2745 wm_hi 125 slack 5.40032 pct_thresh 0.33 intensity_thresh 130.4 nvox_thresh 8.58 139 voxels tested (0.00%) 96 voxels changed (0.00%) removing voxels with positive offset direction... MRIremoveWrongDirection() wsize=3, lowthr=80.2745, hithr=97.0106 smoothing input volume with sigma = 0.250 177937 voxels tested (1.06%) 20240 voxels changed (0.12%) thicken = 1 removing 1-dimensional structures... MRIremove1dStructures(): max_iter=10000, thresh=2, WM_MIN_VAL=5 1862 sparsely connected voxels removed in 1 iterations thickening thin strands.... thickness 4 nsegments 20 wm_hi 125 2096 diagonally connected voxels added... MRIthickenThinWMStrands(): thickness=4, nsegments=20 20 segments, 2302 filled MRIfindBrightNonWM(): 577 bright non-wm voxels segmented. MRIfilterMorphology() WM_MIN_VAL=5, DIAGONAL_FILL=230 white matter segmentation took 1.6 minutes writing output to wm.seg.mgz... @#@FSTIME 2026:03:01:16:56:53 mri_segment N 5 e 93.29 S 0.25 U 92.72 P 99% M 156320 F 0 R 90264 W 0 c 138 w 14 I 0 O 0 L 1.10 1.19 1.17 @#@FSLOADPOST 2026:03:01:16:58:27 mri_segment N 5 1.10 1.18 1.17 mri_edit_wm_with_aseg -keep-in wm.seg.mgz brain.mgz aseg.presurf.mgz wm.asegedit.mgz preserving editing changes in input volume... auto filling took 0.44 minutes reading wm segmentation from wm.seg.mgz... MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab MRIcopyHeader(): source has ctab 0 voxels added to wm to prevent paths from MTL structures to cortex 5549 additional wm voxels added 0 additional wm voxels added SEG EDIT: 105251 voxels turned on, 60483 voxels turned off. propagating editing to output volume from wm.seg.mgz writing edited volume to wm.asegedit.mgz.... @#@FSTIME 2026:03:01:16:58:27 mri_edit_wm_with_aseg N 5 e 26.29 S 0.16 U 26.03 P 99% M 461464 F 0 R 42207 W 0 c 29 w 15 I 0 O 0 L 1.10 1.18 1.17 @#@FSLOADPOST 2026:03:01:16:58:53 mri_edit_wm_with_aseg N 5 1.13 1.18 1.17 mri_pretess wm.asegedit.mgz wm norm.mgz wm.mgz Iteration Number : 1 pass 1 (xy+): 9 found - 9 modified | TOTAL: 9 pass 2 (xy+): 0 found - 9 modified | TOTAL: 9 pass 1 (xy-): 17 found - 17 modified | TOTAL: 26 pass 2 (xy-): 0 found - 17 modified | TOTAL: 26 pass 1 (yz+): 25 found - 25 modified | TOTAL: 51 pass 2 (yz+): 0 found - 25 modified | TOTAL: 51 pass 1 (yz-): 13 found - 13 modified | TOTAL: 64 pass 2 (yz-): 0 found - 13 modified | TOTAL: 64 pass 1 (xz+): 13 found - 13 modified | TOTAL: 77 pass 2 (xz+): 0 found - 13 modified | TOTAL: 77 pass 1 (xz-): 7 found - 7 modified | TOTAL: 84 pass 2 (xz-): 0 found - 7 modified | TOTAL: 84 Iteration Number : 1 pass 1 (+++): 7 found - 7 modified | TOTAL: 7 pass 2 (+++): 0 found - 7 modified | TOTAL: 7 pass 1 (+++): 4 found - 4 modified | TOTAL: 11 pass 2 (+++): 0 found - 4 modified | TOTAL: 11 pass 1 (+++): 0 found - 0 modified | TOTAL: 11 pass 1 (+++): 0 found - 0 modified | TOTAL: 11 Iteration Number : 1 pass 1 (++): 43 found - 43 modified | TOTAL: 43 pass 2 (++): 0 found - 43 modified | TOTAL: 43 pass 1 (+-): 38 found - 38 modified | TOTAL: 81 pass 2 (+-): 0 found - 38 modified | TOTAL: 81 pass 1 (--): 36 found - 36 modified | TOTAL: 117 pass 2 (--): 0 found - 36 modified | TOTAL: 117 pass 1 (-+): 23 found - 23 modified | TOTAL: 140 pass 2 (-+): 0 found - 23 modified | TOTAL: 140 Iteration Number : 2 pass 1 (xy+): 3 found - 3 modified | TOTAL: 3 pass 2 (xy+): 0 found - 3 modified | TOTAL: 3 pass 1 (xy-): 2 found - 2 modified | TOTAL: 5 pass 2 (xy-): 0 found - 2 modified | TOTAL: 5 pass 1 (yz+): 0 found - 0 modified | TOTAL: 5 pass 1 (yz-): 1 found - 1 modified | TOTAL: 6 pass 2 (yz-): 0 found - 1 modified | TOTAL: 6 pass 1 (xz+): 1 found - 1 modified | TOTAL: 7 pass 2 (xz+): 0 found - 1 modified | TOTAL: 7 pass 1 (xz-): 1 found - 1 modified | TOTAL: 8 pass 2 (xz-): 0 found - 1 modified | TOTAL: 8 Iteration Number : 2 pass 1 (+++): 2 found - 2 modified | TOTAL: 2 pass 2 (+++): 0 found - 2 modified | TOTAL: 2 pass 1 (+++): 1 found - 1 modified | TOTAL: 3 pass 2 (+++): 0 found - 1 modified | TOTAL: 3 pass 1 (+++): 0 found - 0 modified | TOTAL: 3 pass 1 (+++): 0 found - 0 modified | TOTAL: 3 Iteration Number : 2 pass 1 (++): 0 found - 0 modified | TOTAL: 0 pass 1 (+-): 0 found - 0 modified | TOTAL: 0 pass 1 (--): 2 found - 2 modified | TOTAL: 2 pass 2 (--): 0 found - 2 modified | TOTAL: 2 pass 1 (-+): 1 found - 1 modified | TOTAL: 3 pass 2 (-+): 0 found - 1 modified | TOTAL: 3 Iteration Number : 3 pass 1 (xy+): 0 found - 0 modified | TOTAL: 0 pass 1 (xy-): 0 found - 0 modified | TOTAL: 0 pass 1 (yz+): 0 found - 0 modified | TOTAL: 0 pass 1 (yz-): 0 found - 0 modified | TOTAL: 0 pass 1 (xz+): 0 found - 0 modified | TOTAL: 0 pass 1 (xz-): 0 found - 0 modified | TOTAL: 0 Iteration Number : 3 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 pass 1 (+++): 0 found - 0 modified | TOTAL: 0 Iteration Number : 3 pass 1 (++): 0 found - 0 modified | TOTAL: 0 pass 1 (+-): 0 found - 0 modified | TOTAL: 0 pass 1 (--): 0 found - 0 modified | TOTAL: 0 pass 1 (-+): 0 found - 0 modified | TOTAL: 0 Total Number of Modified Voxels = 249 (out of 607622: 0.040979) binarizing input wm segmentation... Ambiguous edge configurations... mri_pretess done @#@FSTIME 2026:03:01:16:58:53 mri_pretess N 4 e 2.15 S 0.01 U 2.13 P 99% M 56472 F 0 R 1742 W 0 c 4 w 9 I 0 O 0 L 1.13 1.18 1.17 @#@FSLOADPOST 2026:03:01:16:58:55 mri_pretess N 4 1.13 1.18 1.17 #-------------------------------------------- #@# Fill Sun Mar 1 16:58:55 EST 2026