Fri Feb 16 14:59:56 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm /usr/local/freesurfer/bin/recon-all -i /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/T1w_acpc_dc_restore.nii.gz -T2 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/T2w_acpc_dc_restore.nii.gz -subjid hcptest8_1mm -sd /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w -hires -openmp 8 -all -T2pial subjid hcptest8_1mm setenv SUBJECTS_DIR /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w FREESURFER_HOME /usr/local/freesurfer Actual FREESURFER_HOME /usr/local/freesurfer build-stamp.txt: freesurfer-Linux-centos4_x86_64-stable-pub-v5.3.0 Linux induction.sdsc.edu 2.6.18-419.el5 #1 SMP Fri Feb 24 22:47:42 UTC 2017 x86_64 x86_64 x86_64 GNU/Linux cputime unlimited filesize unlimited datasize unlimited stacksize 10240 kbytes coredumpsize 0 kbytes memoryuse unlimited vmemoryuse unlimited descriptors 1024 memorylocked 32 kbytes maxproc 1031912 total used free shared buffers cached Mem: 132088544 131393624 694920 0 28404 46085996 -/+ buffers/cache: 85279224 46809320 Swap: 2031608 200756 1830852 ######################################## program versions used $Id: recon-all,v 1.379.2.73 2013/05/12 23:15:37 nicks Exp $ $Id: mri_motion_correct.fsl,v 1.14 2011/03/02 20:16:39 nicks Exp $ mri_convert -all-info ProgramName: mri_convert ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:56-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mri_convert.c,v 1.179.2.7 2012/09/05 21:55:16 mreuter Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 FLIRT version 5.5 $Id: talairach_avi,v 1.9 2011/03/02 18:38:06 nicks Exp $ mri_convert --version stable5 ProgramName: tkregister2_cmdl ProgramArguments: --all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:56-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: tkregister2.c,v 1.121.2.1 2011/03/28 20:25:16 greve Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 Program nu_correct, built from: Package MNI N3, version 1.10, compiled by nicks@minerva (x86_64-unknown-linux-gnu) on 2010-02-20 at 17:32:37 ProgramName: mri_make_uchar ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:56-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mri_make_uchar.c,v 1.4 2011/03/02 00:04:14 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mri_normalize ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:57-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mri_normalize.c,v 1.73.2.1 2012/10/17 19:11:32 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mri_watershed ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:57-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mri_watershed.cpp,v 1.96.2.1 2011/11/08 22:18:44 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mri_gcut ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:57-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mri_gcut.cpp,v 1.14 2011/03/02 00:04:16 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mri_segment ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:57-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mri_segment.c,v 1.40 2011/03/02 00:04:24 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mri_label2label ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:57-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mri_label2label.c,v 1.40.2.2 2013/04/02 16:26:15 greve Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mri_em_register ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:57-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mri_em_register.c,v 1.84.2.3 2013/02/09 00:49:26 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mri_ca_normalize ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:57-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mri_ca_normalize.c,v 1.52.2.2 2012/10/17 19:11:32 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mri_ca_register ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:57-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mri_ca_register.c,v 1.78.2.3 2013/02/09 00:42:20 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mri_ca_label ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:57-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mri_ca_label.c,v 1.96.2.1 2012/08/28 22:11:20 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mri_pretess ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:57-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mri_pretess.c,v 1.20 2011/03/02 00:04:23 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mri_fill ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:57-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mri_fill.c,v 1.118 2011/03/16 21:23:49 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mri_tessellate ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:58-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mri_tessellate.c,v 1.36 2011/03/02 00:04:25 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mri_concatenate_lta ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:58-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mri_concatenate_lta.c,v 1.10 2011/03/16 21:23:48 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mri_normalize_tp2 ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:58-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mri_normalize_tp2.c,v 1.8 2011/03/02 00:04:23 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mris_smooth ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:58-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mris_smooth.c,v 1.28 2011/03/02 00:04:34 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mris_inflate ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:58-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mris_inflate.c,v 1.43 2011/03/02 00:04:32 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mris_curvature ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:58-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mris_curvature.c,v 1.31 2011/03/02 00:04:30 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mris_sphere ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:58-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mris_sphere.c,v 1.57 2011/03/02 00:04:34 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mris_fix_topology ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:58-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mris_fix_topology.c,v 1.48 2011/03/02 00:04:32 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mris_topo_fixer ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:58-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mris_topo_fixer.cpp,v 1.29 2011/03/02 00:04:34 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mris_ca_label ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:58-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mris_ca_label.c,v 1.35 2011/03/02 00:04:27 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mris_euler_number ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:58-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mris_euler_number.c,v 1.8.2.2 2013/01/14 22:40:07 greve Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mris_make_surfaces ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:59-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mris_make_surfaces.c,v 1.127.2.6 2013/05/12 22:28:01 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mris_register ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:59-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mris_register.c,v 1.59 2011/03/02 00:04:33 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mris_volmask ProgramArguments: --all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:59-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mris_volmask.cpp,v 1.25 2011/03/02 00:04:34 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mris_anatomical_stats ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:59-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mris_anatomical_stats.c,v 1.72 2011/03/02 00:04:26 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mrisp_paint ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:59-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mrisp_paint.c,v 1.11 2011/03/02 00:04:35 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mris_curvature_stats ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:59-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mris_curvature_stats.c,v 1.64 2011/03/02 00:04:30 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mris_calc ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:59-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mris_calc.c,v 1.37.2.8 2013/01/28 17:05:17 greve Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 $Id: mri_robust_register.cpp,v 1.52.2.3 2012/11/20 17:26:47 mreuter Exp $ ProgramName: mri_robust_register ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:59-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mri_robust_register.cpp,v 1.52.2.3 2012/11/20 17:26:47 mreuter Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 $Id: mri_robust_template.cpp,v 1.37.2.2 2012/10/10 19:59:06 mreuter Exp $ ProgramName: mri_robust_template ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:59-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mri_robust_template.cpp,v 1.37.2.2 2012/10/10 19:59:06 mreuter Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mri_and ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-22:59:59-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mri_and.c,v 1.4 2011/03/02 00:04:13 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mri_or ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-23:00:00-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mri_or.c,v 1.3 2011/03/02 00:04:13 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mri_fuse_segmentations ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-23:00:00-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mri_fuse_segmentations.c,v 1.8 2011/03/02 00:04:15 nicks Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ProgramName: mri_segstats ProgramArguments: -all-info ProgramVersion: $Name: stable5 $ TimeStamp: 2018/02/16-23:00:00-GMT BuildTimeStamp: May 13 2013 18:45:07 CVS: $Id: mri_segstats.c,v 1.75.2.9 2013/02/16 00:09:33 greve Exp $ User: achen Machine: induction.sdsc.edu Platform: Linux PlatformVersion: 2.6.18-419.el5 CompilerName: GCC CompilerVersion: 30400 ####################################### GCADIR /usr/local/freesurfer/average GCA RB_all_2008-03-26.gca GCASkull RB_all_withskull_2008-03-26.gca AvgCurvTif average.curvature.filled.buckner40.tif GCSDIR /usr/local/freesurfer/average GCS curvature.buckner40.filled.desikan_killiany.2010-03-25.gcs ####################################### /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm mri_convert /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/T1w_acpc_dc_restore.nii.gz /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/orig/001.mgz mri_convert /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/T1w_acpc_dc_restore.nii.gz /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/orig/001.mgz $Id: mri_convert.c,v 1.179.2.7 2012/09/05 21:55:16 mreuter Exp $ reading from /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/T1w_acpc_dc_restore.nii.gz... TR=8.78, TE=0.00, TI=0.00, flip angle=0.00 i_ras = (-1, 0, 0) j_ras = (0, 1, 0) k_ras = (0, 0, 1) writing to /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/orig/001.mgz... #-------------------------------------------- #@# T2/FLAIR Input Fri Feb 16 15:00:04 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm mri_convert /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/T2w_acpc_dc_restore.nii.gz /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/orig/T2raw.mgz mri_convert /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/T2w_acpc_dc_restore.nii.gz /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/orig/T2raw.mgz $Id: mri_convert.c,v 1.179.2.7 2012/09/05 21:55:16 mreuter Exp $ reading from /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/T2w_acpc_dc_restore.nii.gz... TR=3200.00, TE=0.00, TI=0.00, flip angle=0.00 i_ras = (-1, 0, 0) j_ras = (0, 1, 0) k_ras = (0, 0, 1) writing to /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/orig/T2raw.mgz... #-------------------------------------------- #@# MotionCor Fri Feb 16 15:00:09 PST 2018 Found 1 runs /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/orig/001.mgz Checking for (invalid) multi-frame inputs... WARNING: only one run found. This is OK, but motion correction cannot be performed on one run, so I'll copy the run to rawavg and continue. cp /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/orig/001.mgz /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/rawavg.mgz /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm mri_convert /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/rawavg.mgz /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/orig.mgz --conform_min mri_convert /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/rawavg.mgz /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/orig.mgz --conform_min $Id: mri_convert.c,v 1.179.2.7 2012/09/05 21:55:16 mreuter Exp $ reading from /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/rawavg.mgz... TR=8.78, TE=0.00, TI=0.00, flip angle=0.00 i_ras = (-1, 0, 0) j_ras = (0, 1, 0) k_ras = (0, 0, 1) Original Data has (1, 1, 1) mm size and (182, 218, 182) voxels. Data is conformed to 1 mm size and 256 voxels for all directions changing data type from float to uchar (noscale = 0)... MRIchangeType: Building histogram Reslicing using trilinear interpolation writing to /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/orig.mgz... mri_add_xform_to_header -c /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/transforms/talairach.xfm /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/orig.mgz /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/orig.mgz INFO: extension is mgz #-------------------------------------------- #@# Talairach Fri Feb 16 15:00:27 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri mri_nu_correct.mni --n 1 --proto-iters 1000 --distance 50 --no-rescale --i orig.mgz --o orig_nu.mgz talairach_avi --i orig_nu.mgz --xfm transforms/talairach.auto.xfm cp transforms/talairach.auto.xfm transforms/talairach.xfm #-------------------------------------------- #@# Talairach Failure Detection Fri Feb 16 15:03:29 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri talairach_afd -T 0.005 -xfm transforms/talairach.xfm talairach_afd: Talairach Transform: transforms/talairach.xfm OK (p=0.6781, pval=0.4932 >= threshold=0.0050) awk -f /usr/local/freesurfer/bin/extract_talairach_avi_QA.awk /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/transforms/talairach_avi.log tal_QC_AZS /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/transforms/talairach_avi.log TalAviQA: 0.97849 z-score: 0 #-------------------------------------------- #@# Nu Intensity Correction Fri Feb 16 15:03:29 PST 2018 mri_nu_correct.mni --i orig.mgz --o nu.mgz --uchar transforms/talairach.xfm --cm --n 2 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri /usr/local/freesurfer/bin/mri_nu_correct.mni --i orig.mgz --o nu.mgz --uchar transforms/talairach.xfm --cm --n 2 nIters 2 $Id: mri_nu_correct.mni,v 1.18.2.1 2013/01/09 21:23:42 nicks Exp $ Linux induction.sdsc.edu 2.6.18-419.el5 #1 SMP Fri Feb 24 22:47:42 UTC 2017 x86_64 x86_64 x86_64 GNU/Linux Fri Feb 16 15:03:29 PST 2018 Program nu_correct, built from: Package MNI N3, version 1.10, compiled by nicks@minerva (x86_64-unknown-linux-gnu) on 2010-02-20 at 17:32:37 tmpdir is ./tmp.mri_nu_correct.mni.9156 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri mri_convert -cm orig.mgz ./tmp.mri_nu_correct.mni.9156/nu0.mnc -odt float mri_convert -cm orig.mgz ./tmp.mri_nu_correct.mni.9156/nu0.mnc -odt float $Id: mri_convert.c,v 1.179.2.7 2012/09/05 21:55:16 mreuter Exp $ reading from orig.mgz... TR=8.78, 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) Original Data has (1, 1, 1) mm size and (256, 256, 256) voxels. Data is conformed to 1 mm size and 256 voxels for all directions changing data type from uchar to float (noscale = 0)... writing to ./tmp.mri_nu_correct.mni.9156/nu0.mnc... -------------------------------------------------------- Iteration 1 Fri Feb 16 15:03:37 PST 2018 nu_correct -clobber ./tmp.mri_nu_correct.mni.9156/nu0.mnc ./tmp.mri_nu_correct.mni.9156/nu1.mnc -tmpdir ./tmp.mri_nu_correct.mni.9156/0/ [achen@induction.sdsc.edu:/data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/] [2018-02-16 15:03:37] running: /usr/local/freesurfer/mni/bin/nu_estimate_np_and_em -parzen -log -sharpen 0.15 0.01 -iterations 50 -stop 0.001 -shrink 4 -auto_mask -nonotify -b_spline 1 -distance 200 -quiet -execute -clobber -nokeeptmp -tmpdir ./tmp.mri_nu_correct.mni.9156/0/ ./tmp.mri_nu_correct.mni.9156/nu0.mnc ./tmp.mri_nu_correct.mni.9156/nu1.imp Processing:.................................................................Done 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Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Number of iterations: 40 CV of field change: 0.000974704 [achen@induction.sdsc.edu:/data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/] [2018-02-16 15:04:19] running: /usr/local/freesurfer/mni/bin/make_template -quiet -shrink 3 ./tmp.mri_nu_correct.mni.9156/nu0.mnc ./tmp.mri_nu_correct.mni.9156/0//template.mnc Transforming slices:......................................................................................Done Transforming slices:................................................................................................................................................................................................................................................................Done -------------------------------------------------------- Iteration 2 Fri Feb 16 15:04:27 PST 2018 nu_correct -clobber ./tmp.mri_nu_correct.mni.9156/nu1.mnc ./tmp.mri_nu_correct.mni.9156/nu2.mnc -tmpdir ./tmp.mri_nu_correct.mni.9156/1/ [achen@induction.sdsc.edu:/data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/] [2018-02-16 15:04:27] running: /usr/local/freesurfer/mni/bin/nu_estimate_np_and_em -parzen -log -sharpen 0.15 0.01 -iterations 50 -stop 0.001 -shrink 4 -auto_mask -nonotify -b_spline 1 -distance 200 -quiet -execute -clobber -nokeeptmp -tmpdir ./tmp.mri_nu_correct.mni.9156/1/ ./tmp.mri_nu_correct.mni.9156/nu1.mnc ./tmp.mri_nu_correct.mni.9156/nu2.imp Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done 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Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Number of iterations: 33 CV of field change: 0.000993107 [achen@induction.sdsc.edu:/data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/] [2018-02-16 15:05:02] running: /usr/local/freesurfer/mni/bin/make_template -quiet -shrink 3 ./tmp.mri_nu_correct.mni.9156/nu1.mnc ./tmp.mri_nu_correct.mni.9156/1//template.mnc Transforming slices:......................................................................................Done Transforming slices:................................................................................................................................................................................................................................................................Done mri_binarize --i ./tmp.mri_nu_correct.mni.9156/nu2.mnc --min -1 --o ./tmp.mri_nu_correct.mni.9156/ones.mgz $Id: mri_binarize.c,v 1.26.2.1 2011/04/08 15:40:50 greve Exp $ cwd /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri cmdline mri_binarize --i ./tmp.mri_nu_correct.mni.9156/nu2.mnc --min -1 --o ./tmp.mri_nu_correct.mni.9156/ones.mgz sysname Linux hostname induction.sdsc.edu machine x86_64 user achen input ./tmp.mri_nu_correct.mni.9156/nu2.mnc frame 0 nErode3d 0 nErode2d 0 output ./tmp.mri_nu_correct.mni.9156/ones.mgz Binarizing based on threshold min -1 max +infinity binval 1 binvalnot 0 Found 16777216 values in range Counting number of voxels Found 16777216 voxels in final mask mri_binarize done mri_segstats --id 1 --seg ./tmp.mri_nu_correct.mni.9156/ones.mgz --i orig.mgz --sum ./tmp.mri_nu_correct.mni.9156/sum.junk --avgwf ./tmp.mri_nu_correct.mni.9156/input.mean.dat $Id: mri_segstats.c,v 1.75.2.9 2013/02/16 00:09:33 greve Exp $ cwd cmdline mri_segstats --id 1 --seg ./tmp.mri_nu_correct.mni.9156/ones.mgz --i orig.mgz --sum ./tmp.mri_nu_correct.mni.9156/sum.junk --avgwf ./tmp.mri_nu_correct.mni.9156/input.mean.dat sysname Linux hostname induction.sdsc.edu machine x86_64 user achen UseRobust 0 Loading ./tmp.mri_nu_correct.mni.9156/ones.mgz Loading orig.mgz Voxel Volume is 1 mm^3 Generating list of segmentation ids Found 1 segmentations Computing statistics for each segmentation 0 1 16777216 16777216.000 Reporting on 1 segmentations Computing spatial average of each frame 0 Writing to ./tmp.mri_nu_correct.mni.9156/input.mean.dat mri_segstats done mri_segstats --id 1 --seg ./tmp.mri_nu_correct.mni.9156/ones.mgz --i ./tmp.mri_nu_correct.mni.9156/nu2.mnc --sum ./tmp.mri_nu_correct.mni.9156/sum.junk --avgwf ./tmp.mri_nu_correct.mni.9156/output.mean.dat $Id: mri_segstats.c,v 1.75.2.9 2013/02/16 00:09:33 greve Exp $ cwd cmdline mri_segstats --id 1 --seg ./tmp.mri_nu_correct.mni.9156/ones.mgz --i ./tmp.mri_nu_correct.mni.9156/nu2.mnc --sum ./tmp.mri_nu_correct.mni.9156/sum.junk --avgwf ./tmp.mri_nu_correct.mni.9156/output.mean.dat sysname Linux hostname induction.sdsc.edu machine x86_64 user achen UseRobust 0 Loading ./tmp.mri_nu_correct.mni.9156/ones.mgz Loading ./tmp.mri_nu_correct.mni.9156/nu2.mnc Voxel Volume is 1 mm^3 Generating list of segmentation ids Found 1 segmentations Computing statistics for each segmentation 0 1 16777216 16777216.000 Reporting on 1 segmentations Computing spatial average of each frame 0 Writing to ./tmp.mri_nu_correct.mni.9156/output.mean.dat mri_segstats done mris_calc -o ./tmp.mri_nu_correct.mni.9156/nu2.mnc ./tmp.mri_nu_correct.mni.9156/nu2.mnc mul .91389688971421558184 Saving result to './tmp.mri_nu_correct.mni.9156/nu2.mnc' (type = MINC ) [ ok ] mri_convert -cm ./tmp.mri_nu_correct.mni.9156/nu2.mnc nu.mgz --like orig.mgz mri_convert -cm ./tmp.mri_nu_correct.mni.9156/nu2.mnc nu.mgz --like orig.mgz $Id: mri_convert.c,v 1.179.2.7 2012/09/05 21:55:16 mreuter Exp $ reading from ./tmp.mri_nu_correct.mni.9156/nu2.mnc... TR=0.00, 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) Original Data has (1, 1, 1) mm size and (256, 256, 256) voxels. Data is conformed to 1 mm size and 256 voxels for all directions INFO: transform src into the like-volume: orig.mgz changing data type from float to uchar (noscale = 0)... MRIchangeType: Building histogram writing to nu.mgz... Fri Feb 16 15:06:25 PST 2018 mri_nu_correct.mni done mri_add_xform_to_header -c /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/transforms/talairach.xfm nu.mgz nu.mgz INFO: extension is mgz #-------------------------------------------- #@# Intensity Normalization Fri Feb 16 15:06:28 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri mri_normalize -g 1 -noconform nu.mgz T1.mgz using max gradient = 1.000 not interpolating and embedding volume to be 256^3... reading from nu.mgz... normalizing image... talairach transform 1.005 -0.003 0.010 -0.175; 0.006 1.052 0.032 -2.250; -0.027 0.038 1.154 2.810; 0.000 0.000 0.000 1.000; processing without aseg, no1d=0 MRInormInit(): INFO: Modifying talairach volume c_(r,a,s) based on average_305 MRInormalize(): MRIsplineNormalize(): npeaks = 19 Starting OpenSpline(): npoints = 19 building Voronoi diagram... performing soap bubble smoothing, sigma = 8... Iterating 2 times --------------------------------- 3d normalization pass 1 of 2 white matter peak found at 111 white matter peak found at 108 gm peak at 82 (82), valley at 58 (58) csf peak at 21, setting threshold to 61 building Voronoi diagram... performing soap bubble smoothing, sigma = 8... --------------------------------- 3d normalization pass 2 of 2 white matter peak found at 111 white matter peak found at 109 gm peak at 82 (82), valley at 59 (59) csf peak at 21, setting threshold to 61 building Voronoi diagram... performing soap bubble smoothing, sigma = 8... Done iterating --------------------------------- writing output to T1.mgz 3D bias adjustment took 2 minutes and 46 seconds. #-------------------------------------------- #@# Skull Stripping Fri Feb 16 15:09:16 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri mri_watershed -T1 T1.mgz brainmask.auto.mgz Mode: T1 normalized volume ********************************************************* The input file is T1.mgz The output file is brainmask.auto.mgz *************************WATERSHED************************** Sorting... T1-weighted MRI image modification of the preflooding height to 15 percent Count how many 110 voxels are present : 130987 Find the largest 110-component... heap usage = 770104 Kbytes. current max segment has 40717 voxels heap usage = 777124 Kbytes. current max segment has 43718 voxels heap usage = 787376 Kbytes. current max segment has 47613 voxels heap usage = 807160 Kbytes. current max segment has 53951 voxels heap usage = 835012 Kbytes. current max segment has 63797 voxels removing small segments (less than 1 percent of maxarea). heap usage = 827248 Kbytes. removing small segments (less than 1 percent of maxarea).done And identify it as the main brain basin...done Main component: 63797 voxels first estimation of the COG coord: x=125 y=134 z=134 r=91 first estimation of the main basin volume: 3236262 voxels global maximum in x=91, y=130, z=102, Imax=255 CSF=19, WM_intensity=110, WM_VARIANCE=5 WM_MIN=110, WM_HALF_MIN=110, WM_HALF_MAX=110, WM_MAX=110 preflooding height equal to 15 percent done. Analyze... main basin size= 1453388 voxels, voxel volume =1.000 = 1453388 mmm3 = 1453.388 cm3 done. PostAnalyze... ***** 0 basin(s) merged in 1 iteration(s) ***** 0 voxel(s) added to the main basin done. ****************TEMPLATE DEFORMATION**************** second estimation of the COG coord: x=127,y=135, z=128, r=9267 iterations ^^^^^^^^ couldn't find WM with original limits - expanding ^^^^^^ GLOBAL CSF_MIN=13, CSF_intensity=23, CSF_MAX=50 , nb = 41346 CSF_MAX TRANSITION GM_MIN GM GLOBAL before analyzing : 50, 60, 66, 81 after analyzing : 50, 64, 66, 68 mri_strip_skull: done peeling brain highly tesselated surface with 10242 vertices matching...67 iterations *********************VALIDATION********************* curvature mean = -0.014, std = 0.012 curvature mean = 67.642, std = 10.325 No Rigid alignment: -atlas Mode Off (basic atlas / no registration) before rotation: sse = 15.13, sigma = 32.41 after rotation: sse = 15.13, sigma = 32.41 Localization of inacurate regions: Erosion-Dilation steps the sse mean is 18.09, its var is 30.46 before Erosion-Dilatation 19.02% of inacurate vertices after Erosion-Dilatation 26.01% of inacurate vertices 14.15% of 'positive' inacurate vertices 85.85% of 'negative' inacurate vertices The surface validation has detected a possible Error If the final segmentation is not valid, try using the option '-atlas' Scaling of atlas fields onto current surface fields ********FINAL ITERATIVE TEMPLATE DEFORMATION******** Compute Local values csf/gray Fine Segmentation...40 iterations mri_strip_skull: done peeling brain Brain Size = 1423085 voxels, voxel volume = 1.000 mm3 = 1423085 mmm3 = 1423.085 cm3 ****************************** Saving brainmask.auto.mgz done cp brainmask.auto.mgz brainmask.mgz #------------------------------------- #@# EM Registration Fri Feb 16 15:10:11 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri mri_em_register -uns 3 -mask brainmask.mgz nu.mgz /usr/local/freesurfer/average/RB_all_2008-03-26.gca transforms/talairach.lta aligning to atlas containing skull, setting unknown_nbr_spacing = 3 using MR volume brainmask.mgz to mask input volume... reading 1 input volumes... logging results to talairach.log reading '/usr/local/freesurfer/average/RB_all_2008-03-26.gca'... average std = 6.9 using min determinant for regularization = 4.7 0 singular and 1812 ill-conditioned covariance matrices regularized reading 'nu.mgz'... freeing gibbs priors...done. bounding unknown intensity as < 14.9 or > 790.2 total sample mean = 84.4 (994 zeros) ************************************************ spacing=8, using 2772 sample points, tol=1.00e-05... ************************************************ register_mri: find_optimal_transform find_optimal_transform: nsamples 2772, passno 0, spacing 8 resetting wm mean[0]: 102 --> 107 resetting gm mean[0]: 64 --> 64 input volume #1 is the most T1-like using real data threshold=37.8 skull bounding box = (55, 84, 42) --> (197, 170, 209) using (102, 113, 126) as brain centroid... mean wm in atlas = 107, using box (85,103,105) --> (119, 123,146) to find MRI wm before smoothing, mri peak at 133 after smoothing, mri peak at 132, scaling input intensities by 0.811 scaling channel 0 by 0.810606 initial log_p = -4.8 ************************************************ First Search limited to translation only. ************************************************ max log p = -4.180527 @ (-9.091, -27.273, -27.273) max log p = -4.013734 @ (4.545, -4.545, 4.545) max log p = -3.862119 @ (2.273, 6.818, 2.273) max log p = -3.862119 @ (0.000, 0.000, 0.000) max log p = -3.862119 @ (0.000, 0.000, 0.000) max log p = -3.862119 @ (0.000, 0.000, 0.000) Found translation: (-2.3, -25.0, -20.5): log p = -3.862 **************************************** Nine parameter search. iteration 0 nscales = 0 ... **************************************** Result so far: scale 1.000: max_log_p=-3.8, old_max_log_p =-3.9 (thresh=-3.9) 1.000 0.000 0.000 -2.273; 0.000 1.150 0.000 -46.580; 0.000 0.000 1.000 -20.455; 0.000 0.000 0.000 1.000; **************************************** Nine parameter search. iteration 1 nscales = 0 ... **************************************** Result so far: scale 1.000: max_log_p=-3.8, old_max_log_p =-3.8 (thresh=-3.8) 1.000 0.000 0.000 -2.273; 0.000 1.150 0.000 -46.580; 0.000 0.000 1.000 -20.455; 0.000 0.000 0.000 1.000; reducing scale to 0.2500 **************************************** Nine parameter search. iteration 2 nscales = 1 ... **************************************** Result so far: scale 0.250: max_log_p=-3.7, old_max_log_p =-3.8 (thresh=-3.8) 0.944 0.000 0.000 4.897; 0.000 1.171 -0.033 -43.524; 0.000 0.038 0.999 -23.925; 0.000 0.000 0.000 1.000; **************************************** Nine parameter search. iteration 3 nscales = 1 ... **************************************** Result so far: scale 0.250: max_log_p=-3.7, old_max_log_p =-3.7 (thresh=-3.7) 0.944 0.000 0.000 4.897; 0.000 1.171 -0.033 -43.524; 0.000 0.038 0.999 -23.925; 0.000 0.000 0.000 1.000; reducing scale to 0.0625 **************************************** Nine parameter search. iteration 4 nscales = 2 ... **************************************** Result so far: scale 0.062: max_log_p=-3.7, old_max_log_p =-3.7 (thresh=-3.7) 0.942 -0.009 0.008 5.011; 0.008 1.170 -0.025 -45.852; -0.008 0.028 1.003 -22.045; 0.000 0.000 0.000 1.000; **************************************** Nine parameter search. iteration 5 nscales = 2 ... **************************************** Result so far: scale 0.062: max_log_p=-3.7, old_max_log_p =-3.7 (thresh=-3.7) 0.942 -0.009 0.008 5.011; 0.008 1.170 -0.025 -45.852; -0.008 0.028 1.003 -22.045; 0.000 0.000 0.000 1.000; min search scale 0.025000 reached *********************************************** Computing MAP estimate using 2772 samples... *********************************************** dt = 5.00e-06, momentum=0.80, tol=1.00e-05 l_intensity = 1.0000 Aligning input volume to GCA... Transform matrix 0.94218 -0.00935 0.00840 5.01066; 0.00770 1.16979 -0.02504 -45.85241; -0.00772 0.02817 1.00319 -22.04519; 0.00000 0.00000 0.00000 1.00000; nsamples 2772 Quasinewton: input matrix 0.94218 -0.00935 0.00840 5.01066; 0.00770 1.16979 -0.02504 -45.85241; -0.00772 0.02817 1.00319 -22.04519; 0.00000 0.00000 0.00000 1.00000; IFLAG= -1 LINE SEARCH FAILED. SEE DOCUMENTATION OF ROUTINE MCSRCH ERROR RETURN OF LINE SEARCH: INFO= 3 POSSIBLE CAUSES: FUNCTION OR GRADIENT ARE INCORRECT OR INCORRECT TOLERANCESoutof QuasiNewtonEMA: 008: -log(p) = -0.0 tol 0.000010 Resulting transform: 0.942 -0.009 0.008 5.011; 0.008 1.170 -0.025 -45.852; -0.008 0.028 1.003 -22.045; 0.000 0.000 0.000 1.000; pass 1, spacing 8: log(p) = -3.7 (old=-4.8) transform before final EM align: 0.942 -0.009 0.008 5.011; 0.008 1.170 -0.025 -45.852; -0.008 0.028 1.003 -22.045; 0.000 0.000 0.000 1.000; ************************************************** EM alignment process ... Computing final MAP estimate using 312841 samples. ************************************************** dt = 5.00e-06, momentum=0.80, tol=1.00e-07 l_intensity = 1.0000 Aligning input volume to GCA... Transform matrix 0.94218 -0.00935 0.00840 5.01066; 0.00770 1.16979 -0.02504 -45.85241; -0.00772 0.02817 1.00319 -22.04519; 0.00000 0.00000 0.00000 1.00000; nsamples 312841 Quasinewton: input matrix 0.94218 -0.00935 0.00840 5.01066; 0.00770 1.16979 -0.02504 -45.85241; -0.00772 0.02817 1.00319 -22.04519; 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: 010: -log(p) = 4.1 tol 0.000000 final transform: 0.942 -0.009 0.008 5.011; 0.008 1.170 -0.025 -45.852; -0.008 0.028 1.003 -22.045; 0.000 0.000 0.000 1.000; writing output transformation to transforms/talairach.lta... registration took 29 minutes and 10 seconds. #-------------------------------------- #@# CA Normalize Fri Feb 16 15:39:21 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri mri_ca_normalize -c ctrl_pts.mgz -mask brainmask.mgz nu.mgz /usr/local/freesurfer/average/RB_all_2008-03-26.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 '/usr/local/freesurfer/average/RB_all_2008-03-26.gca'... reading transform from 'transforms/talairach.lta'... reading input volume from nu.mgz... resetting wm mean[0]: 102 --> 107 resetting gm mean[0]: 64 --> 64 input volume #1 is the most T1-like using real data threshold=37.8 skull bounding box = (55, 84, 42) --> (197, 171, 209) using (102, 113, 126) as brain centroid... mean wm in atlas = 107, using box (85,102,105) --> (119, 123,146) to find MRI wm before smoothing, mri peak at 133 after smoothing, mri peak at 132, scaling input intensities by 0.811 scaling channel 0 by 0.810606 using 244171 sample points... INFO: compute sample coordinates transform 0.942 -0.009 0.008 5.011; 0.008 1.170 -0.025 -45.852; -0.008 0.028 1.003 -22.045; 0.000 0.000 0.000 1.000; INFO: transform used finding control points in Left_Cerebral_White_Matter.... found 41584 control points for structure... bounding box (127, 85, 44) --> (199, 187, 212) Left_Cerebral_White_Matter: limiting intensities to 90.0 --> 206.0 0 of 16 (0.0%) samples deleted finding control points in Right_Cerebral_White_Matter.... found 40735 control points for structure... bounding box (60, 85, 45) --> (129, 187, 212) Right_Cerebral_White_Matter: limiting intensities to 93.0 --> 206.0 0 of 9 (0.0%) samples deleted finding control points in Left_Cerebellum_White_Matter.... found 3012 control points for structure... bounding box (131, 155, 66) --> (183, 192, 120) finding control points in Right_Cerebellum_White_Matter.... found 2764 control points for structure... bounding box (81, 155, 64) --> (129, 193, 120) finding control points in Brain_Stem.... found 3520 control points for structure... bounding box (112, 152, 99) --> (146, 210, 132) using 25 total control points for intensity normalization... bias field = 1.042 +- 0.061 0 of 25 control points discarded finding control points in Left_Cerebral_White_Matter.... found 41584 control points for structure... bounding box (127, 85, 44) --> (199, 187, 212) Left_Cerebral_White_Matter: limiting intensities to 99.0 --> 202.0 0 of 99 (0.0%) samples deleted finding control points in Right_Cerebral_White_Matter.... found 40735 control points for structure... bounding box (60, 85, 45) --> (129, 187, 212) Right_Cerebral_White_Matter: limiting intensities to 98.0 --> 202.0 0 of 90 (0.0%) samples deleted finding control points in Left_Cerebellum_White_Matter.... found 3012 control points for structure... bounding box (131, 155, 66) --> (183, 192, 120) finding control points in Right_Cerebellum_White_Matter.... found 2764 control points for structure... bounding box (81, 155, 64) --> (129, 193, 120) finding control points in Brain_Stem.... found 3520 control points for structure... bounding box (112, 152, 99) --> (146, 210, 132) using 189 total control points for intensity normalization... bias field = 0.977 +- 0.052 0 of 189 control points discarded finding control points in Left_Cerebral_White_Matter.... found 41584 control points for structure... bounding box (127, 85, 44) --> (199, 187, 212) Left_Cerebral_White_Matter: limiting intensities to 94.0 --> 187.0 0 of 191 (0.0%) samples deleted finding control points in Right_Cerebral_White_Matter.... found 40735 control points for structure... bounding box (60, 85, 45) --> (129, 187, 212) Right_Cerebral_White_Matter: limiting intensities to 92.0 --> 187.0 0 of 223 (0.0%) samples deleted finding control points in Left_Cerebellum_White_Matter.... found 3012 control points for structure... bounding box (131, 155, 66) --> (183, 192, 120) finding control points in Right_Cerebellum_White_Matter.... found 2764 control points for structure... bounding box (81, 155, 64) --> (129, 193, 120) finding control points in Brain_Stem.... found 3520 control points for structure... bounding box (112, 152, 99) --> (146, 210, 132) using 414 total control points for intensity normalization... bias field = 1.005 +- 0.043 0 of 414 control points discarded writing normalized volume to norm.mgz... writing control points to ctrl_pts.mgz freeing GCA...done. normalization took 2 minutes and 16 seconds. #-------------------------------------- #@# CA Reg Fri Feb 16 15:41:37 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri mri_ca_register -nobigventricles -T transforms/talairach.lta -align-after -mask brainmask.mgz norm.mgz /usr/local/freesurfer/average/RB_all_2008-03-26.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... reading 1 input volumes... logging results to talairach.log reading input volume 'norm.mgz'... reading GCA '/usr/local/freesurfer/average/RB_all_2008-03-26.gca'... label assignment complete, 0 changed (0.00%) det(m_affine) = 1.11 (predicted orig area = 7.2) label assignment complete, 0 changed (0.00%) freeing gibbs priors...done. average std[0] = 5.0 **************** pass 1 of 1 ************************ setting smoothness coefficient to 0.039 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=1.054, neg=0, invalid=96777 0001: dt=129.472000, rms=0.976 (7.380%), neg=0, invalid=96777 0002: dt=369.920000, rms=0.934 (4.266%), neg=0, invalid=96777 0003: dt=295.936000, rms=0.882 (5.555%), neg=0, invalid=96777 0004: dt=129.472000, rms=0.851 (3.503%), neg=0, invalid=96777 0005: dt=129.472000, rms=0.834 (2.072%), neg=0, invalid=96777 0006: dt=129.472000, rms=0.822 (1.455%), neg=0, invalid=96777 0007: dt=369.920000, rms=0.796 (3.159%), neg=0, invalid=96777 0008: dt=92.480000, rms=0.795 (0.075%), neg=0, invalid=96777 0009: dt=92.480000, rms=0.789 (0.703%), neg=0, invalid=96777 0010: dt=92.480000, rms=0.783 (0.772%), neg=0, invalid=96777 0011: dt=92.480000, rms=0.778 (0.747%), neg=0, invalid=96777 0012: dt=92.480000, rms=0.772 (0.741%), neg=0, invalid=96777 0013: dt=92.480000, rms=0.766 (0.769%), neg=0, invalid=96777 0014: dt=92.480000, rms=0.762 (0.563%), neg=0, invalid=96777 0015: dt=92.480000, rms=0.758 (0.523%), neg=0, invalid=96777 0016: dt=92.480000, rms=0.754 (0.408%), neg=0, invalid=96777 0017: dt=92.480000, rms=0.750 (0.547%), neg=0, invalid=96777 0018: dt=92.480000, rms=0.747 (0.447%), neg=0, invalid=96777 0019: dt=92.480000, rms=0.745 (0.251%), neg=0, invalid=96777 0020: dt=92.480000, rms=0.741 (0.615%), neg=0, invalid=96777 0021: dt=92.480000, rms=0.734 (0.863%), neg=0, invalid=96777 0022: dt=92.480000, rms=0.730 (0.499%), neg=0, invalid=96777 0023: dt=92.480000, rms=0.729 (0.189%), neg=0, invalid=96777 0024: dt=92.480000, rms=0.725 (0.507%), neg=0, invalid=96777 0025: dt=92.480000, rms=0.721 (0.552%), neg=0, invalid=96777 0026: dt=92.480000, rms=0.721 (0.048%), neg=0, invalid=96777 0027: dt=92.480000, rms=0.721 (-0.210%), neg=0, invalid=96777 0028: dt=6.936000, rms=0.721 (0.000%), neg=0, invalid=96777 0029: dt=129.472000, rms=0.721 (0.064%), neg=0, invalid=96777 0030: dt=887.808000, rms=0.716 (0.611%), neg=0, invalid=96777 0031: dt=0.000000, rms=0.716 (-0.005%), neg=0, invalid=96777 0032: dt=0.850000, rms=0.716 (-0.002%), neg=0, invalid=96777 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.716, neg=0, invalid=96777 0033: dt=23.120000, rms=0.716 (0.038%), neg=0, invalid=96777 0034: dt=32.368000, rms=0.716 (0.046%), neg=0, invalid=96777 0035: dt=92.480000, rms=0.715 (0.060%), neg=0, invalid=96777 0036: dt=517.888000, rms=0.712 (0.504%), neg=0, invalid=96777 0037: dt=0.000000, rms=0.712 (-0.004%), neg=0, invalid=96777 0038: dt=0.850000, rms=0.712 (-0.002%), neg=0, invalid=96777 setting smoothness coefficient to 0.154 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.725, neg=0, invalid=96777 0039: dt=0.000000, rms=0.725 (0.000%), neg=0, invalid=96777 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.725, neg=0, invalid=96777 0040: dt=0.000000, rms=0.725 (0.000%), neg=0, invalid=96777 setting smoothness coefficient to 0.588 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.774, neg=0, invalid=96777 0041: dt=0.750000, rms=0.774 (0.055%), neg=0, invalid=96777 0042: dt=9.064846, rms=0.768 (0.730%), neg=0, invalid=96777 0043: dt=2.000000, rms=0.763 (0.696%), neg=0, invalid=96777 0044: dt=2.800000, rms=0.760 (0.302%), neg=0, invalid=96777 0045: dt=2.800000, rms=0.755 (0.662%), neg=0, invalid=96777 0046: dt=2.800000, rms=0.754 (0.173%), neg=0, invalid=96777 0047: dt=2.800000, rms=0.749 (0.587%), neg=0, invalid=96777 0048: dt=2.800000, rms=0.744 (0.708%), neg=0, invalid=96777 0049: dt=2.800000, rms=0.741 (0.442%), neg=0, invalid=96777 0050: dt=2.800000, rms=0.736 (0.718%), neg=0, invalid=96777 0051: dt=2.800000, rms=0.733 (0.395%), neg=0, invalid=96777 0052: dt=2.800000, rms=0.729 (0.484%), neg=0, invalid=96777 0053: dt=2.800000, rms=0.726 (0.410%), neg=0, invalid=96777 0054: dt=2.800000, rms=0.723 (0.382%), neg=0, invalid=96777 0055: dt=2.800000, rms=0.721 (0.377%), neg=0, invalid=96777 0056: dt=2.800000, rms=0.717 (0.490%), neg=0, invalid=96777 0057: dt=2.800000, rms=0.713 (0.564%), neg=0, invalid=96777 0058: dt=2.800000, rms=0.709 (0.539%), neg=0, invalid=96777 0059: dt=2.800000, rms=0.707 (0.383%), neg=0, invalid=96777 0060: dt=2.800000, rms=0.704 (0.300%), neg=0, invalid=96777 0061: dt=2.800000, rms=0.703 (0.246%), neg=0, invalid=96777 0062: dt=2.800000, rms=0.702 (0.108%), neg=0, invalid=96777 0063: dt=2.800000, rms=0.701 (0.100%), neg=0, invalid=96777 0064: dt=11.200000, rms=0.699 (0.364%), neg=0, invalid=96777 0065: dt=0.000000, rms=0.699 (-0.000%), neg=0, invalid=96777 0066: dt=0.250000, rms=0.699 (-0.032%), neg=0, invalid=96777 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.699, neg=0, invalid=96777 0067: dt=0.000000, rms=0.699 (0.000%), neg=0, invalid=96777 setting smoothness coefficient to 2.000 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.810, neg=0, invalid=96777 0068: dt=0.000000, rms=0.810 (0.000%), neg=0, invalid=96777 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.810, neg=0, invalid=96777 0069: dt=0.000000, rms=0.810 (0.000%), neg=0, invalid=96777 setting smoothness coefficient to 5.000 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=1.006, neg=0, invalid=96777 0070: dt=0.028000, rms=1.005 (0.085%), neg=0, invalid=96777 0071: dt=0.112000, rms=1.002 (0.307%), neg=0, invalid=96777 0072: dt=0.028000, rms=1.001 (0.070%), neg=0, invalid=96777 0073: dt=0.028000, rms=1.000 (0.065%), neg=0, invalid=96777 0074: dt=0.028000, rms=0.999 (0.121%), neg=0, invalid=96777 0075: dt=0.028000, rms=0.998 (0.158%), neg=0, invalid=96777 0076: dt=0.028000, rms=0.996 (0.182%), neg=0, invalid=96777 0077: dt=0.028000, rms=0.994 (0.189%), neg=0, invalid=96777 0078: dt=0.028000, rms=0.992 (0.184%), neg=0, invalid=96777 0079: dt=0.028000, rms=0.990 (0.167%), neg=0, invalid=96777 0080: dt=0.028000, rms=0.989 (0.140%), neg=0, invalid=96777 0081: dt=0.028000, rms=0.988 (0.115%), neg=0, invalid=96777 0082: dt=0.028000, rms=0.987 (0.085%), neg=0, invalid=96777 0083: dt=0.833333, rms=0.984 (0.302%), neg=0, invalid=96777 0084: dt=0.112000, rms=0.984 (0.024%), neg=0, invalid=96777 0085: dt=0.112000, rms=0.984 (0.025%), neg=0, invalid=96777 0086: dt=0.112000, rms=0.983 (0.047%), neg=0, invalid=96777 0087: dt=0.112000, rms=0.983 (0.058%), neg=0, invalid=96777 0088: dt=0.112000, rms=0.982 (0.065%), neg=0, invalid=96777 0089: dt=0.112000, rms=0.981 (0.063%), neg=0, invalid=96777 0090: dt=0.112000, rms=0.981 (0.051%), neg=0, invalid=96777 0091: dt=0.112000, rms=0.981 (0.022%), neg=0, invalid=96777 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.981, neg=0, invalid=96777 0092: dt=0.448000, rms=0.979 (0.176%), neg=0, invalid=96777 0093: dt=0.112000, rms=0.979 (0.031%), neg=0, invalid=96777 0094: dt=0.112000, rms=0.978 (0.030%), neg=0, invalid=96777 0095: dt=0.112000, rms=0.978 (0.053%), neg=0, invalid=96777 0096: dt=0.112000, rms=0.977 (0.070%), neg=0, invalid=96777 0097: dt=0.112000, rms=0.976 (0.079%), neg=0, invalid=96777 0098: dt=0.112000, rms=0.975 (0.080%), neg=0, invalid=96777 0099: dt=0.112000, rms=0.975 (0.079%), neg=0, invalid=96777 0100: dt=0.112000, rms=0.974 (0.080%), neg=0, invalid=96777 0101: dt=0.112000, rms=0.973 (0.075%), neg=0, invalid=96777 resetting metric properties... setting smoothness coefficient to 10.000 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.782, neg=0, invalid=96777 0102: dt=0.146505, rms=0.775 (0.911%), neg=0, invalid=96777 0103: dt=0.448000, rms=0.770 (0.611%), neg=0, invalid=96777 0104: dt=0.127671, rms=0.764 (0.789%), neg=0, invalid=96777 0105: dt=0.016000, rms=0.764 (0.003%), neg=0, invalid=96777 0106: dt=0.016000, rms=0.764 (0.002%), neg=0, invalid=96777 0107: dt=0.016000, rms=0.764 (0.005%), neg=0, invalid=96777 0108: dt=0.016000, rms=0.764 (0.010%), neg=0, invalid=96777 0109: dt=0.016000, rms=0.764 (0.019%), neg=0, invalid=96777 0110: dt=0.016000, rms=0.763 (0.042%), neg=0, invalid=96777 0111: dt=0.016000, rms=0.763 (0.070%), neg=0, invalid=96777 0112: dt=0.016000, rms=0.762 (0.102%), neg=0, invalid=96777 0113: dt=0.016000, rms=0.761 (0.131%), neg=0, invalid=96777 0114: dt=0.016000, rms=0.760 (0.149%), neg=0, invalid=96777 0115: dt=0.016000, rms=0.759 (0.159%), neg=0, invalid=96777 0116: dt=0.016000, rms=0.758 (0.158%), neg=0, invalid=96777 0117: dt=0.016000, rms=0.756 (0.153%), neg=0, invalid=96777 0118: dt=0.016000, rms=0.755 (0.146%), neg=0, invalid=96777 0119: dt=0.016000, rms=0.754 (0.133%), neg=0, invalid=96777 0120: dt=0.016000, rms=0.753 (0.123%), neg=0, invalid=96777 0121: dt=0.016000, rms=0.753 (0.113%), neg=0, invalid=96777 0122: dt=0.500000, rms=0.752 (0.094%), neg=0, invalid=96777 0123: dt=0.062500, rms=0.751 (0.182%), neg=0, invalid=96777 0124: dt=0.062500, rms=0.749 (0.189%), neg=0, invalid=96777 0125: dt=0.062500, rms=0.748 (0.130%), neg=0, invalid=96777 0126: dt=0.062500, rms=0.748 (0.078%), neg=0, invalid=96777 0127: dt=0.062500, rms=0.748 (-0.026%), neg=0, invalid=96777 0128: dt=0.000000, rms=0.748 (0.000%), neg=0, invalid=96777 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.748, neg=0, invalid=96777 0129: dt=0.112000, rms=0.746 (0.151%), neg=0, invalid=96777 0130: dt=0.028000, rms=0.746 (0.012%), neg=0, invalid=96777 0131: dt=0.014000, rms=0.746 (0.004%), neg=0, invalid=96777 0132: dt=0.014000, rms=0.746 (0.004%), neg=0, invalid=96777 0133: dt=0.014000, rms=0.746 (0.009%), neg=0, invalid=96777 0134: dt=0.014000, rms=0.746 (0.011%), neg=0, invalid=96777 0135: dt=0.014000, rms=0.746 (0.014%), neg=0, invalid=96777 0136: dt=0.007000, rms=0.746 (0.002%), neg=0, invalid=96777 renormalizing by structure alignment.... renormalizing input #0 gca peak = 0.11725 (24) mri peak = 0.11006 (36) Left_Lateral_Ventricle (4): linear fit = 1.51 x + 0.0 (2006 voxels, overlap=0.203) Left_Lateral_Ventricle (4): linear fit = 1.50 x + 0.0 (2006 voxels, peak = 36), gca=36.0 gca peak = 0.14022 (22) mri peak = 0.13184 (37) Right_Lateral_Ventricle (43): linear fit = 1.51 x + 0.0 (1067 voxels, overlap=0.105) Right_Lateral_Ventricle (43): linear fit = 1.50 x + 0.0 (1067 voxels, peak = 33), gca=33.0 gca peak = 0.24234 (100) mri peak = 0.08190 (95) Right_Pallidum (52): linear fit = 0.95 x + 0.0 (380 voxels, overlap=1.007) Right_Pallidum (52): linear fit = 0.95 x + 0.0 (380 voxels, peak = 96), gca=95.5 gca peak = 0.19192 (97) mri peak = 0.08731 (86) Left_Pallidum (13): linear fit = 0.88 x + 0.0 (362 voxels, overlap=0.052) Left_Pallidum (13): linear fit = 0.88 x + 0.0 (362 voxels, peak = 86), gca=85.8 gca peak = 0.24007 (63) mri peak = 0.04948 (81) Right_Hippocampus (53): linear fit = 1.25 x + 0.0 (520 voxels, overlap=0.019) Right_Hippocampus (53): linear fit = 1.25 x + 0.0 (520 voxels, peak = 78), gca=78.4 gca peak = 0.29892 (64) mri peak = 0.06385 (79) Left_Hippocampus (17): linear fit = 1.20 x + 0.0 (437 voxels, overlap=0.019) Left_Hippocampus (17): linear fit = 1.20 x + 0.0 (437 voxels, peak = 76), gca=76.5 gca peak = 0.12541 (104) mri peak = 0.08276 (105) Right_Cerebral_White_Matter (41): linear fit = 1.01 x + 0.0 (81339 voxels, overlap=0.812) Right_Cerebral_White_Matter (41): linear fit = 1.01 x + 0.0 (81339 voxels, peak = 106), gca=105.6 gca peak = 0.13686 (104) mri peak = 0.07724 (105) Left_Cerebral_White_Matter (2): linear fit = 1.01 x + 0.0 (79261 voxels, overlap=0.824) Left_Cerebral_White_Matter (2): linear fit = 1.01 x + 0.0 (79261 voxels, peak = 106), gca=105.6 gca peak = 0.11691 (63) mri peak = 0.04344 (79) Left_Cerebral_Cortex (3): linear fit = 1.25 x + 0.0 (25654 voxels, overlap=0.055) Left_Cerebral_Cortex (3): linear fit = 1.25 x + 0.0 (25654 voxels, peak = 78), gca=78.4 gca peak = 0.13270 (63) mri peak = 0.04884 (78) Right_Cerebral_Cortex (42): linear fit = 1.23 x + 0.0 (31298 voxels, overlap=0.043) Right_Cerebral_Cortex (42): linear fit = 1.23 x + 0.0 (31298 voxels, peak = 77), gca=77.2 gca peak = 0.15182 (70) mri peak = 0.09658 (82) Right_Caudate (50): linear fit = 1.13 x + 0.0 (469 voxels, overlap=0.205) Right_Caudate (50): linear fit = 1.13 x + 0.0 (469 voxels, peak = 79), gca=79.4 gca peak = 0.14251 (76) mri peak = 0.09903 (100) Left_Caudate (11): linear fit = 1.20 x + 0.0 (710 voxels, overlap=0.435) Left_Caudate (11): linear fit = 1.20 x + 0.0 (710 voxels, peak = 91), gca=90.8 gca peak = 0.12116 (60) mri peak = 0.05628 (78) Left_Cerebellum_Cortex (8): linear fit = 1.27 x + 0.0 (534 voxels, overlap=0.049) Left_Cerebellum_Cortex (8): linear fit = 1.27 x + 0.0 (534 voxels, peak = 76), gca=76.5 gca peak = 0.12723 (61) mri peak = 0.05216 (95) gca peak = 0.22684 (88) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.21067 (87) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.25455 (62) mri peak = 0.09211 (82) Left_Amygdala (18): linear fit = 1.25 x + 0.0 (312 voxels, overlap=0.079) Left_Amygdala (18): linear fit = 1.25 x + 0.0 (312 voxels, peak = 77), gca=77.2 gca peak = 0.39668 (62) mri peak = 0.09603 (76) Right_Amygdala (54): linear fit = 1.26 x + 0.0 (304 voxels, overlap=0.059) Right_Amygdala (54): linear fit = 1.26 x + 0.0 (304 voxels, peak = 78), gca=78.4 gca peak = 0.10129 (93) mri peak = 0.08071 (101) Left_Thalamus_Proper (10): linear fit = 1.10 x + 0.0 (5579 voxels, overlap=0.412) Left_Thalamus_Proper (10): linear fit = 1.10 x + 0.0 (5579 voxels, peak = 102), gca=101.8 gca peak = 0.12071 (89) mri peak = 0.06361 (97) Right_Thalamus_Proper (49): linear fit = 1.10 x + 0.0 (3788 voxels, overlap=0.479) Right_Thalamus_Proper (49): linear fit = 1.10 x + 0.0 (3788 voxels, peak = 97), gca=97.5 gca peak = 0.13716 (82) mri peak = 0.05210 (91) Left_Putamen (12): linear fit = 1.10 x + 0.0 (2363 voxels, overlap=0.795) Left_Putamen (12): linear fit = 1.10 x + 0.0 (2363 voxels, peak = 90), gca=89.8 gca peak = 0.15214 (84) mri peak = 0.06871 (88) Right_Putamen (51): linear fit = 1.07 x + 0.0 (2456 voxels, overlap=0.857) Right_Putamen (51): linear fit = 1.07 x + 0.0 (2456 voxels, peak = 89), gca=89.5 gca peak = 0.08983 (85) mri peak = 0.09887 (103) Brain_Stem (16): linear fit = 1.21 x + 0.0 (1102 voxels, overlap=0.006) Brain_Stem (16): linear fit = 1.21 x + 0.0 (1102 voxels, peak = 102), gca=102.4 gca peak = 0.11809 (92) mri peak = 0.08835 (99) Right_VentralDC (60): linear fit = 1.12 x + 0.0 (751 voxels, overlap=0.453) Right_VentralDC (60): linear fit = 1.12 x + 0.0 (751 voxels, peak = 103), gca=102.6 gca peak = 0.12914 (94) mri peak = 0.07846 (105) Left_VentralDC (28): linear fit = 1.08 x + 0.0 (937 voxels, overlap=0.591) Left_VentralDC (28): linear fit = 1.08 x + 0.0 (937 voxels, peak = 101), gca=101.1 gca peak = 0.21100 (36) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.13542 (27) uniform distribution in MR - rejecting arbitrary fit gca peak Unknown = 0.94427 ( 0) gca peak Left_Inf_Lat_Vent = 0.21802 (40) gca peak Left_Cerebellum_White_Matter = 0.22684 (88) gca peak Third_Ventricle = 0.21100 (36) gca peak Fourth_Ventricle = 0.13542 (27) gca peak CSF = 0.17123 (45) gca peak Left_Accumbens_area = 0.25875 (69) gca peak Left_undetermined = 0.96240 (36) gca peak Left_vessel = 0.33262 (65) gca peak Left_choroid_plexus = 0.09846 (46) gca peak Right_Inf_Lat_Vent = 0.28113 (34) gca peak Right_Cerebellum_White_Matter = 0.21067 (87) gca peak Right_Cerebellum_Cortex = 0.12723 (61) gca peak Right_Accumbens_area = 0.27120 (72) gca peak Right_vessel = 0.61915 (60) gca peak Right_choroid_plexus = 0.12775 (51) gca peak Fifth_Ventricle = 0.45329 (44) gca peak WM_hypointensities = 0.11729 (81) gca peak non_WM_hypointensities = 0.10912 (56) gca peak Optic_Chiasm = 0.33287 (75) label assignment complete, 0 changed (0.00%) not using caudate to estimate GM means setting label Right_Cerebellum_Cortex based on Left_Cerebellum_Cortex = 1.27 x + 0: 76 estimating mean gm scale to be 1.24 x + 0.0 estimating mean wm scale to be 1.01 x + 0.0 estimating mean csf scale to be 1.50 x + 0.0 saving intensity scales to talairach.label_intensities.txt **************** pass 1 of 1 ************************ setting smoothness coefficient to 0.008 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.767, neg=0, invalid=96777 0137: dt=23.120000, rms=0.725 (5.488%), neg=0, invalid=96777 0138: dt=0.590909, rms=0.725 (0.064%), neg=0, invalid=96777 0139: dt=0.505750, rms=0.725 (0.056%), neg=0, invalid=96777 0140: dt=0.000000, rms=0.725 (-0.000%), neg=0, invalid=96777 0141: dt=0.001660, rms=0.725 (0.000%), neg=0, invalid=96777 0142: dt=0.000415, rms=0.725 (0.000%), neg=0, invalid=96777 0143: dt=0.000104, rms=0.725 (0.000%), neg=0, invalid=96777 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.725, neg=0, invalid=96777 0144: dt=0.000000, rms=0.725 (0.000%), neg=0, invalid=96777 setting smoothness coefficient to 0.031 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.725, neg=0, invalid=96777 0145: dt=0.000000, rms=0.725 (0.000%), neg=0, invalid=96777 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.725, neg=0, invalid=96777 0146: dt=0.000000, rms=0.725 (0.000%), neg=0, invalid=96777 setting smoothness coefficient to 0.118 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.725, neg=0, invalid=96777 0147: dt=2.000000, rms=0.712 (1.687%), neg=0, invalid=96777 0148: dt=0.700000, rms=0.709 (0.520%), neg=0, invalid=96777 0149: dt=0.175000, rms=0.708 (0.125%), neg=0, invalid=96777 0150: dt=0.175000, rms=0.707 (0.120%), neg=0, invalid=96777 0151: dt=0.043750, rms=0.707 (0.032%), neg=0, invalid=96777 0152: dt=0.000684, rms=0.707 (0.000%), neg=0, invalid=96777 0153: dt=0.000342, rms=0.707 (-0.000%), neg=0, invalid=96777 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.707, neg=0, invalid=96777 0154: dt=2.800000, rms=0.697 (1.323%), neg=0, invalid=96777 0155: dt=0.175000, rms=0.697 (0.073%), neg=0, invalid=96777 0156: dt=0.009375, rms=0.697 (0.004%), neg=0, invalid=96777 0157: dt=0.000586, rms=0.697 (0.000%), neg=0, invalid=96777 0158: dt=0.000146, rms=0.697 (0.000%), neg=0, invalid=96777 0159: dt=0.000018, rms=0.697 (0.000%), neg=0, invalid=96777 0160: dt=0.000000, rms=0.697 (0.000%), neg=0, invalid=96777 setting smoothness coefficient to 0.400 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.697, neg=0, invalid=96777 0161: dt=0.252000, rms=0.695 (0.346%), neg=0, invalid=96777 0162: dt=0.252000, rms=0.692 (0.352%), neg=0, invalid=96777 0163: dt=0.252000, rms=0.690 (0.348%), neg=0, invalid=96777 0164: dt=1.008000, rms=0.680 (1.375%), neg=0, invalid=96777 0165: dt=0.252000, rms=0.678 (0.324%), neg=0, invalid=96777 0166: dt=1.008000, rms=0.670 (1.265%), neg=0, invalid=96777 0167: dt=0.252000, rms=0.668 (0.294%), neg=0, invalid=96777 0168: dt=0.252000, rms=0.666 (0.291%), neg=0, invalid=96777 0169: dt=0.864000, rms=0.659 (0.992%), neg=0, invalid=96777 0170: dt=0.252000, rms=0.657 (0.273%), neg=0, invalid=96777 0171: dt=0.720000, rms=0.652 (0.771%), neg=0, invalid=96777 0172: dt=0.252000, rms=0.650 (0.258%), neg=0, invalid=96777 0173: dt=1.008000, rms=0.644 (1.020%), neg=0, invalid=96777 0174: dt=0.252000, rms=0.642 (0.236%), neg=0, invalid=96777 0175: dt=0.252000, rms=0.641 (0.232%), neg=0, invalid=96777 0176: dt=0.252000, rms=0.639 (0.227%), neg=0, invalid=96777 0177: dt=0.720000, rms=0.635 (0.641%), neg=0, invalid=96777 0178: dt=0.180000, rms=0.634 (0.151%), neg=0, invalid=96777 0179: dt=0.180000, rms=0.633 (0.150%), neg=0, invalid=96777 0180: dt=0.252000, rms=0.632 (0.208%), neg=0, invalid=96777 0181: dt=0.720000, rms=0.628 (0.571%), neg=0, invalid=96777 0182: dt=0.252000, rms=0.627 (0.192%), neg=0, invalid=96777 0183: dt=0.720000, rms=0.624 (0.533%), neg=0, invalid=96777 0184: dt=0.216000, rms=0.623 (0.151%), neg=0, invalid=96777 0185: dt=0.216000, rms=0.622 (0.150%), neg=0, invalid=96777 0186: dt=0.252000, rms=0.621 (0.173%), neg=0, invalid=96777 0187: dt=0.864000, rms=0.617 (0.581%), neg=0, invalid=96777 0188: dt=0.252000, rms=0.616 (0.160%), neg=0, invalid=96777 0189: dt=0.252000, rms=0.615 (0.158%), neg=0, invalid=96777 0190: dt=0.252000, rms=0.614 (0.155%), neg=0, invalid=96777 0191: dt=1.008000, rms=0.611 (0.615%), neg=0, invalid=96777 0192: dt=0.252000, rms=0.610 (0.143%), neg=0, invalid=96777 0193: dt=0.252000, rms=0.609 (0.142%), neg=0, invalid=96777 0194: dt=0.252000, rms=0.608 (0.139%), neg=0, invalid=96777 0195: dt=1.008000, rms=0.605 (0.543%), neg=0, invalid=96777 0196: dt=0.252000, rms=0.604 (0.126%), neg=0, invalid=96777 0197: dt=0.252000, rms=0.603 (0.123%), neg=0, invalid=96777 0198: dt=0.720000, rms=0.601 (0.344%), neg=0, invalid=96777 0199: dt=0.063000, rms=0.601 (0.030%), neg=0, invalid=96777 0200: dt=0.063000, rms=0.601 (0.028%), neg=0, invalid=96777 0201: dt=0.063000, rms=0.601 (0.055%), neg=0, invalid=96777 0202: dt=0.063000, rms=0.600 (0.077%), neg=0, invalid=96777 0203: dt=0.063000, rms=0.599 (0.098%), neg=0, invalid=96777 0204: dt=0.063000, rms=0.599 (0.114%), neg=0, invalid=96777 0205: dt=0.063000, rms=0.598 (0.131%), neg=0, invalid=96777 0206: dt=0.063000, rms=0.597 (0.146%), neg=0, invalid=96777 0207: dt=0.063000, rms=0.596 (0.158%), neg=0, invalid=96777 0208: dt=0.063000, rms=0.595 (0.166%), neg=0, invalid=96777 0209: dt=0.063000, rms=0.594 (0.175%), neg=0, invalid=96777 0210: dt=0.063000, rms=0.593 (0.183%), neg=0, invalid=96777 0211: dt=0.063000, rms=0.592 (0.186%), neg=0, invalid=96777 0212: dt=0.063000, rms=0.591 (0.191%), neg=0, invalid=96777 0213: dt=0.063000, rms=0.590 (0.195%), neg=0, invalid=96777 0214: dt=0.063000, rms=0.589 (0.193%), neg=0, invalid=96777 0215: dt=0.063000, rms=0.587 (0.194%), neg=0, invalid=96777 0216: dt=0.063000, rms=0.586 (0.198%), neg=0, invalid=96777 0217: dt=0.063000, rms=0.585 (0.196%), neg=0, invalid=96777 0218: dt=0.063000, rms=0.584 (0.193%), neg=0, invalid=96777 0219: dt=0.063000, rms=0.583 (0.189%), neg=0, invalid=96777 0220: dt=0.063000, rms=0.582 (0.185%), neg=0, invalid=96777 0221: dt=0.063000, rms=0.581 (0.185%), neg=0, invalid=96777 0222: dt=0.063000, rms=0.580 (0.181%), neg=0, invalid=96777 0223: dt=0.063000, rms=0.579 (0.176%), neg=0, invalid=96777 0224: dt=0.063000, rms=0.578 (0.174%), neg=0, invalid=96777 0225: dt=0.063000, rms=0.577 (0.166%), neg=0, invalid=96777 0226: dt=0.063000, rms=0.576 (0.166%), neg=0, invalid=96777 0227: dt=0.063000, rms=0.575 (0.159%), neg=0, invalid=96777 0228: dt=0.063000, rms=0.574 (0.154%), neg=0, invalid=96777 0229: dt=0.063000, rms=0.573 (0.152%), neg=0, invalid=96777 0230: dt=0.063000, rms=0.572 (0.147%), neg=0, invalid=96777 0231: dt=0.063000, rms=0.571 (0.141%), neg=0, invalid=96777 0232: dt=0.063000, rms=0.571 (0.134%), neg=0, invalid=96777 0233: dt=0.063000, rms=0.570 (0.132%), neg=0, invalid=96777 0234: dt=0.063000, rms=0.569 (0.128%), neg=0, invalid=96777 0235: dt=0.063000, rms=0.568 (0.123%), neg=0, invalid=96777 0236: dt=0.063000, rms=0.568 (0.118%), neg=0, invalid=96777 0237: dt=0.063000, rms=0.567 (0.117%), neg=0, invalid=96777 0238: dt=0.063000, rms=0.566 (0.111%), neg=0, invalid=96777 0239: dt=0.063000, rms=0.566 (0.106%), neg=0, invalid=96777 0240: dt=0.063000, rms=0.565 (0.104%), neg=0, invalid=96777 0241: dt=0.063000, rms=0.565 (0.101%), neg=0, invalid=96777 0242: dt=0.063000, rms=0.564 (0.095%), neg=0, invalid=96777 0243: dt=0.063000, rms=0.564 (0.094%), neg=0, invalid=96777 0244: dt=0.063000, rms=0.563 (0.091%), neg=0, invalid=96777 0245: dt=0.063000, rms=0.563 (0.088%), neg=0, invalid=96777 0246: dt=0.063000, rms=0.562 (0.084%), neg=0, invalid=96777 0247: dt=0.063000, rms=0.562 (0.083%), neg=0, invalid=96777 0248: dt=0.063000, rms=0.561 (0.081%), neg=0, invalid=96777 0249: dt=0.063000, rms=0.561 (0.078%), neg=0, invalid=96777 0250: dt=0.063000, rms=0.560 (0.075%), neg=0, invalid=96777 0251: dt=0.063000, rms=0.560 (0.073%), neg=0, invalid=96777 0252: dt=0.063000, rms=0.560 (0.072%), neg=0, invalid=96777 0253: dt=0.063000, rms=0.559 (0.071%), neg=0, invalid=96777 0254: dt=0.063000, rms=0.559 (0.069%), neg=0, invalid=96777 0255: dt=0.063000, rms=0.558 (0.065%), neg=0, invalid=96777 0256: dt=0.063000, rms=0.558 (0.067%), neg=0, invalid=96777 0257: dt=0.063000, rms=0.558 (0.062%), neg=0, invalid=96777 0258: dt=0.063000, rms=0.557 (0.061%), neg=0, invalid=96777 0259: dt=0.063000, rms=0.557 (0.057%), neg=0, invalid=96777 0260: dt=0.063000, rms=0.557 (0.056%), neg=0, invalid=96777 0261: dt=0.063000, rms=0.556 (0.053%), neg=0, invalid=96777 0262: dt=0.063000, rms=0.556 (0.055%), neg=0, invalid=96777 0263: dt=0.063000, rms=0.556 (0.051%), neg=0, invalid=96777 0264: dt=0.063000, rms=0.556 (0.050%), neg=0, invalid=96777 0265: dt=0.063000, rms=0.555 (0.048%), neg=0, invalid=96777 0266: dt=0.063000, rms=0.555 (0.046%), neg=0, invalid=96777 0267: dt=0.063000, rms=0.555 (0.045%), neg=0, invalid=96777 0268: dt=0.063000, rms=0.555 (0.045%), neg=0, invalid=96777 0269: dt=0.063000, rms=0.554 (0.041%), neg=0, invalid=96777 0270: dt=0.063000, rms=0.554 (0.042%), neg=0, invalid=96777 0271: dt=0.063000, rms=0.554 (0.040%), neg=0, invalid=96777 0272: dt=0.063000, rms=0.554 (0.038%), neg=0, invalid=96777 0273: dt=0.063000, rms=0.553 (0.037%), neg=0, invalid=96777 0274: dt=0.063000, rms=0.553 (0.036%), neg=0, invalid=96777 0275: dt=0.063000, rms=0.553 (0.036%), neg=0, invalid=96777 0276: dt=0.063000, rms=0.553 (0.036%), neg=0, invalid=96777 0277: dt=0.063000, rms=0.553 (0.034%), neg=0, invalid=96777 0278: dt=0.063000, rms=0.552 (0.033%), neg=0, invalid=96777 0279: dt=0.063000, rms=0.552 (0.033%), neg=0, invalid=96777 0280: dt=0.063000, rms=0.552 (0.030%), neg=0, invalid=96777 0281: dt=0.063000, rms=0.552 (0.034%), neg=0, invalid=96777 0282: dt=0.063000, rms=0.552 (0.032%), neg=0, invalid=96777 0283: dt=0.063000, rms=0.552 (0.031%), neg=0, invalid=96777 0284: dt=0.063000, rms=0.551 (0.028%), neg=0, invalid=96777 0285: dt=0.063000, rms=0.551 (0.030%), neg=0, invalid=96777 0286: dt=0.063000, rms=0.551 (0.030%), neg=0, invalid=96777 0287: dt=0.063000, rms=0.551 (0.027%), neg=0, invalid=96777 0288: dt=0.063000, rms=0.551 (0.028%), neg=0, invalid=96777 0289: dt=0.063000, rms=0.551 (0.025%), neg=0, invalid=96777 0290: dt=0.063000, rms=0.551 (0.027%), neg=0, invalid=96777 0291: dt=0.063000, rms=0.550 (0.025%), neg=0, invalid=96777 0292: dt=0.063000, rms=0.550 (0.025%), neg=0, invalid=96777 0293: dt=0.063000, rms=0.550 (0.026%), neg=0, invalid=96777 0294: dt=0.063000, rms=0.550 (0.025%), neg=0, invalid=96777 0295: dt=0.063000, rms=0.550 (0.023%), neg=0, invalid=96777 0296: dt=16.128000, rms=0.547 (0.498%), neg=0, invalid=96777 0297: dt=0.864000, rms=0.547 (0.014%), neg=0, invalid=96777 0298: dt=0.108000, rms=0.547 (0.003%), neg=0, invalid=96777 0299: dt=0.108000, rms=0.547 (0.004%), neg=0, invalid=96777 0300: dt=0.108000, rms=0.547 (0.006%), neg=0, invalid=96777 0301: dt=0.108000, rms=0.547 (0.006%), neg=0, invalid=96777 0302: dt=0.108000, rms=0.547 (0.010%), neg=0, invalid=96777 0303: dt=0.108000, rms=0.547 (0.011%), neg=0, invalid=96777 0304: dt=0.108000, rms=0.547 (0.013%), neg=0, invalid=96777 0305: dt=0.108000, rms=0.547 (0.013%), neg=0, invalid=96777 0306: dt=0.108000, rms=0.547 (0.016%), neg=0, invalid=96777 0307: dt=0.108000, rms=0.546 (0.015%), neg=0, invalid=96777 0308: dt=1.008000, rms=0.546 (0.021%), neg=0, invalid=96777 0309: dt=0.063000, rms=0.546 (0.000%), neg=0, invalid=96777 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.546, neg=0, invalid=96777 0310: dt=0.252000, rms=0.546 (0.004%), neg=0, invalid=96777 0311: dt=1.008000, rms=0.546 (0.006%), neg=0, invalid=96777 0312: dt=0.063000, rms=0.546 (0.002%), neg=0, invalid=96777 0313: dt=0.063000, rms=0.546 (0.001%), neg=0, invalid=96777 0314: dt=0.063000, rms=0.546 (0.001%), neg=0, invalid=96777 0315: dt=0.063000, rms=0.546 (0.003%), neg=0, invalid=96777 0316: dt=0.063000, rms=0.546 (0.005%), neg=0, invalid=96777 0317: dt=0.063000, rms=0.546 (0.003%), neg=0, invalid=96777 setting smoothness coefficient to 1.000 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.565, neg=0, invalid=96777 0318: dt=0.000000, rms=0.565 (0.001%), neg=0, invalid=96777 0319: dt=0.000000, rms=0.565 (0.000%), neg=0, invalid=96777 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.565, neg=0, invalid=96777 0320: dt=0.000000, rms=0.565 (0.000%), neg=0, invalid=96777 resetting metric properties... setting smoothness coefficient to 2.000 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.533, neg=0, invalid=96777 0321: dt=0.112000, rms=0.529 (0.752%), neg=0, invalid=96777 0322: dt=0.112000, rms=0.526 (0.598%), neg=0, invalid=96777 0323: dt=0.001750, rms=0.526 (0.008%), neg=0, invalid=96777 0324: dt=0.001750, rms=0.526 (0.008%), neg=0, invalid=96777 0325: dt=0.001750, rms=0.526 (0.014%), neg=0, invalid=96777 0326: dt=0.001750, rms=0.526 (0.022%), neg=0, invalid=96777 0327: dt=0.001750, rms=0.525 (0.026%), neg=0, invalid=96777 0328: dt=0.001750, rms=0.525 (0.031%), neg=0, invalid=96777 0329: dt=0.001750, rms=0.525 (0.034%), neg=0, invalid=96777 0330: dt=0.001750, rms=0.525 (0.039%), neg=0, invalid=96777 0331: dt=0.001750, rms=0.525 (0.041%), neg=0, invalid=96777 0332: dt=0.001750, rms=0.524 (0.045%), neg=0, invalid=96777 0333: dt=0.001750, rms=0.524 (0.045%), neg=0, invalid=96777 0334: dt=0.001750, rms=0.524 (0.049%), neg=0, invalid=96777 0335: dt=0.001750, rms=0.524 (0.051%), neg=0, invalid=96777 0336: dt=0.001750, rms=0.523 (0.052%), neg=0, invalid=96777 0337: dt=0.001750, rms=0.523 (0.053%), neg=0, invalid=96777 0338: dt=0.001750, rms=0.523 (0.054%), neg=0, invalid=96777 0339: dt=0.001750, rms=0.523 (0.052%), neg=0, invalid=96777 0340: dt=0.001750, rms=0.522 (0.053%), neg=0, invalid=96777 0341: dt=0.001750, rms=0.522 (0.055%), neg=0, invalid=96777 0342: dt=0.001750, rms=0.522 (0.056%), neg=0, invalid=96777 0343: dt=0.001750, rms=0.521 (0.056%), neg=0, invalid=96777 0344: dt=0.001750, rms=0.521 (0.054%), neg=0, invalid=96777 0345: dt=0.001750, rms=0.521 (0.053%), neg=0, invalid=96777 0346: dt=0.001750, rms=0.521 (0.054%), neg=0, invalid=96777 0347: dt=0.001750, rms=0.520 (0.050%), neg=0, invalid=96777 0348: dt=0.001750, rms=0.520 (0.055%), neg=0, invalid=96777 0349: dt=0.001750, rms=0.520 (0.052%), neg=0, invalid=96777 0350: dt=0.001750, rms=0.520 (0.047%), neg=0, invalid=96777 0351: dt=0.001750, rms=0.519 (0.053%), neg=0, invalid=96777 0352: dt=0.001750, rms=0.519 (0.047%), neg=0, invalid=96777 0353: dt=0.001750, rms=0.519 (0.047%), neg=0, invalid=96777 0354: dt=0.001750, rms=0.519 (0.048%), neg=0, invalid=96777 0355: dt=0.001750, rms=0.518 (0.044%), neg=0, invalid=96777 0356: dt=0.001750, rms=0.518 (0.044%), neg=0, invalid=96777 0357: dt=0.001750, rms=0.518 (0.043%), neg=0, invalid=96777 0358: dt=0.001750, rms=0.518 (0.044%), neg=0, invalid=96777 0359: dt=0.001750, rms=0.517 (0.041%), neg=0, invalid=96777 0360: dt=0.001750, rms=0.517 (0.040%), neg=0, invalid=96777 0361: dt=0.001750, rms=0.517 (0.040%), neg=0, invalid=96777 0362: dt=0.001750, rms=0.517 (0.038%), neg=0, invalid=96777 0363: dt=0.001750, rms=0.517 (0.036%), neg=0, invalid=96777 0364: dt=0.001750, rms=0.516 (0.037%), neg=0, invalid=96777 0365: dt=0.001750, rms=0.516 (0.037%), neg=0, invalid=96777 0366: dt=0.001750, rms=0.516 (0.034%), neg=0, invalid=96777 0367: dt=0.001750, rms=0.516 (0.034%), neg=0, invalid=96777 0368: dt=0.001750, rms=0.516 (0.033%), neg=0, invalid=96777 0369: dt=0.001750, rms=0.516 (0.031%), neg=0, invalid=96777 0370: dt=0.001750, rms=0.515 (0.030%), neg=0, invalid=96777 0371: dt=0.001750, rms=0.515 (0.031%), neg=0, invalid=96777 0372: dt=0.001750, rms=0.515 (0.029%), neg=0, invalid=96777 0373: dt=0.001750, rms=0.515 (0.029%), neg=0, invalid=96777 0374: dt=0.001750, rms=0.515 (0.027%), neg=0, invalid=96777 0375: dt=0.001750, rms=0.515 (0.027%), neg=0, invalid=96777 0376: dt=0.001750, rms=0.515 (0.028%), neg=0, invalid=96777 0377: dt=0.001750, rms=0.514 (0.022%), neg=0, invalid=96777 0378: dt=0.001750, rms=0.514 (0.025%), neg=0, invalid=96777 0379: dt=0.001750, rms=0.514 (0.025%), neg=0, invalid=96777 0380: dt=0.001750, rms=0.514 (0.025%), neg=0, invalid=96777 0381: dt=0.028000, rms=0.514 (0.026%), neg=0, invalid=96777 0382: dt=0.007000, rms=0.514 (0.003%), neg=0, invalid=96777 0383: dt=0.001750, rms=0.514 (0.004%), neg=0, invalid=96777 0384: dt=0.001750, rms=0.514 (0.003%), neg=0, invalid=96777 0385: dt=0.001750, rms=0.514 (0.003%), neg=0, invalid=96777 0386: dt=0.001750, rms=0.514 (0.003%), neg=0, invalid=96777 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.514, neg=0, invalid=96777 0387: dt=0.007000, rms=0.514 (0.024%), neg=0, invalid=96777 0388: dt=0.006000, rms=0.514 (0.021%), neg=0, invalid=96777 0389: dt=0.006000, rms=0.513 (0.021%), neg=0, invalid=96777 0390: dt=0.006000, rms=0.513 (0.038%), neg=0, invalid=96777 0391: dt=0.006000, rms=0.513 (0.050%), neg=0, invalid=96777 0392: dt=0.003000, rms=0.513 (0.010%), neg=0, invalid=96777 0393: dt=0.001500, rms=0.513 (0.005%), neg=0, invalid=96777 0394: dt=0.006000, rms=0.513 (0.020%), neg=0, invalid=96777 0395: dt=0.007000, rms=0.513 (0.020%), neg=0, invalid=96777 0396: dt=0.003500, rms=0.513 (0.010%), neg=0, invalid=96777 0397: dt=0.003500, rms=0.513 (0.020%), neg=0, invalid=96777 0398: dt=0.003500, rms=0.512 (0.028%), neg=0, invalid=96777 0399: dt=0.003500, rms=0.512 (0.035%), neg=0, invalid=96777 0400: dt=0.003500, rms=0.512 (0.043%), neg=0, invalid=96777 0401: dt=0.003500, rms=0.512 (0.049%), neg=0, invalid=96777 0402: dt=0.003500, rms=0.512 (0.051%), neg=0, invalid=96777 0403: dt=0.003500, rms=0.511 (0.054%), neg=0, invalid=96777 0404: dt=0.003500, rms=0.511 (0.058%), neg=0, invalid=96777 0405: dt=0.003500, rms=0.511 (0.063%), neg=0, invalid=96777 0406: dt=0.003500, rms=0.510 (0.060%), neg=0, invalid=96777 0407: dt=0.003500, rms=0.510 (0.061%), neg=0, invalid=96777 0408: dt=0.003500, rms=0.510 (0.069%), neg=0, invalid=96777 0409: dt=0.003500, rms=0.509 (0.065%), neg=0, invalid=96777 0410: dt=0.003500, rms=0.509 (0.067%), neg=0, invalid=96777 0411: dt=0.003500, rms=0.509 (0.061%), neg=0, invalid=96777 0412: dt=0.003500, rms=0.508 (0.062%), neg=0, invalid=96777 0413: dt=0.003500, rms=0.508 (0.060%), neg=0, invalid=96777 0414: dt=0.003500, rms=0.508 (0.059%), neg=0, invalid=96777 0415: dt=0.003500, rms=0.507 (0.059%), neg=0, invalid=96777 0416: dt=0.003500, rms=0.507 (0.056%), neg=0, invalid=96777 0417: dt=0.003500, rms=0.507 (0.059%), neg=0, invalid=96777 0418: dt=0.003500, rms=0.507 (0.051%), neg=0, invalid=96777 0419: dt=0.003500, rms=0.506 (0.050%), neg=0, invalid=96777 0420: dt=0.003500, rms=0.506 (0.048%), neg=0, invalid=96777 0421: dt=0.003500, rms=0.506 (0.045%), neg=0, invalid=96777 0422: dt=0.003500, rms=0.506 (0.045%), neg=0, invalid=96777 0423: dt=0.003500, rms=0.505 (0.041%), neg=0, invalid=96777 0424: dt=0.003500, rms=0.505 (0.040%), neg=0, invalid=96777 0425: dt=0.003500, rms=0.505 (0.036%), neg=0, invalid=96777 0426: dt=0.003500, rms=0.505 (0.034%), neg=0, invalid=96777 0427: dt=0.003500, rms=0.505 (0.034%), neg=0, invalid=96777 0428: dt=0.003500, rms=0.505 (0.032%), neg=0, invalid=96777 0429: dt=0.003500, rms=0.504 (0.027%), neg=0, invalid=96777 0430: dt=0.003500, rms=0.504 (0.028%), neg=0, invalid=96777 0431: dt=0.003500, rms=0.504 (0.027%), neg=0, invalid=96777 0432: dt=0.003500, rms=0.504 (0.022%), neg=0, invalid=96777 0433: dt=0.003500, rms=0.504 (0.024%), neg=0, invalid=96777 0434: dt=0.003500, rms=0.504 (0.019%), neg=0, invalid=96777 0435: dt=0.007000, rms=0.504 (0.002%), neg=0, invalid=96777 0436: dt=0.003500, rms=0.504 (0.001%), neg=0, invalid=96777 0437: dt=0.003500, rms=0.504 (0.000%), neg=0, invalid=96777 0438: dt=0.003500, rms=0.504 (0.003%), neg=0, invalid=96777 0439: dt=0.003500, rms=0.504 (0.002%), neg=0, invalid=96777 label assignment complete, 0 changed (0.00%) ********************************************************************************************* ********************************************************************************************* ********************************************************************************************* ********************* ALLOWING NEGATIVE NODES IN DEFORMATION ******************************** ********************************************************************************************* ********************************************************************************************* ********************************************************************************************* **************** pass 1 of 1 ************************ setting smoothness coefficient to 0.008 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.502, neg=0, invalid=96777 iter 0, gcam->neg = 1 after 11 iterations, nbhd size=2, neg = 0 0440: dt=32.368000, rms=0.501 (0.297%), neg=0, invalid=96777 iter 0, gcam->neg = 164 after 200 iterations, nbhd size=3, neg = 1 starting rms=0.005, neg=1, removing folds in lattice.... iter 1, dt=0.000055: new neg 0, old_neg 1, delta 1, rms=0.004 (25.738%) 0441: dt=73.984000, rms=0.500 (0.109%), neg=0, invalid=96777 0442: dt=73.984000, rms=0.500 (0.078%), neg=0, invalid=96777 iter 0, gcam->neg = 72 after 200 iterations, nbhd size=1, neg = 17 starting rms=0.006, neg=17, removing folds in lattice.... iter 1, dt=0.000023: new neg 2, old_neg 17, delta 15, rms=0.004 (32.559%) iter 2, dt=0.000031: new neg 0, old_neg 2, delta 2, rms=0.004 (9.220%) 0443: dt=73.984000, rms=0.499 (0.033%), neg=0, invalid=96777 0444: dt=73.984000, rms=0.499 (0.008%), neg=0, invalid=96777 0445: dt=6.936000, rms=0.499 (0.006%), neg=0, invalid=96777 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.499, neg=0, invalid=96777 iter 0, gcam->neg = 6 after 200 iterations, nbhd size=3, neg = 34 starting rms=0.008, neg=34, removing folds in lattice.... iter 1, dt=0.000023: new neg 9, old_neg 34, delta 25, rms=0.005 (34.475%) iter 2, dt=0.000020: new neg 0, old_neg 9, delta 9, rms=0.005 (12.089%) 0446: dt=110.976000, rms=0.499 (0.069%), neg=0, invalid=96777 0447: dt=3.468000, rms=0.499 (-0.003%), neg=0, invalid=96777 setting smoothness coefficient to 0.031 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.499, neg=0, invalid=96777 0448: dt=0.567000, rms=0.499 (0.002%), neg=0, invalid=96777 iter 0, gcam->neg = 62 after 200 iterations, nbhd size=1, neg = 38 starting rms=0.009, neg=38, removing folds in lattice.... iter 1, dt=0.000023: new neg 12, old_neg 38, delta 26, rms=0.007 (28.659%) iter 2, dt=0.000020: new neg 0, old_neg 12, delta 12, rms=0.006 (10.330%) 0449: dt=15.552000, rms=0.499 (0.103%), neg=0, invalid=96777 0450: dt=0.405000, rms=0.499 (0.003%), neg=0, invalid=96777 0451: dt=0.405000, rms=0.499 (0.002%), neg=0, invalid=96777 0452: dt=0.405000, rms=0.499 (0.002%), neg=0, invalid=96777 0453: dt=0.405000, rms=0.498 (0.007%), neg=0, invalid=96777 0454: dt=0.405000, rms=0.498 (0.007%), neg=0, invalid=96777 0455: dt=0.405000, rms=0.498 (0.009%), neg=0, invalid=96777 0456: dt=0.405000, rms=0.498 (0.012%), neg=0, invalid=96777 0457: dt=0.405000, rms=0.498 (0.007%), neg=0, invalid=96777 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.498, neg=0, invalid=96777 iter 0, gcam->neg = 148 after 200 iterations, nbhd size=1, neg = 22 starting rms=0.007, neg=22, removing folds in lattice.... iter 1, dt=0.000023: new neg 2, old_neg 22, delta 20, rms=0.005 (29.245%) iter 2, dt=0.000036: new neg 1, old_neg 2, delta 1, rms=0.005 (7.677%) iter 3, dt=0.000036: new neg 0, old_neg 1, delta 1, rms=0.004 (5.772%) 0458: dt=36.288000, rms=0.497 (0.212%), neg=0, invalid=96777 iter 0, gcam->neg = 1 after 0 iterations, nbhd size=0, neg = 0 0459: dt=2.268000, rms=0.497 (-0.001%), neg=0, invalid=96777 setting smoothness coefficient to 0.118 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.497, neg=0, invalid=96777 iter 0, gcam->neg = 42 after 10 iterations, nbhd size=1, neg = 0 0460: dt=0.500000, rms=0.497 (0.030%), neg=0, invalid=96777 iter 0, gcam->neg = 6 after 200 iterations, nbhd size=2, neg = 8 starting rms=0.004, neg=8, removing folds in lattice.... iter 1, dt=0.000039: new neg 1, old_neg 8, delta 7, rms=0.003 (20.995%) iter 2, dt=0.000036: new neg 0, old_neg 1, delta 1, rms=0.003 (5.051%) 0461: dt=0.700000, rms=0.497 (0.030%), neg=0, invalid=96777 iter 0, gcam->neg = 67 after 38 iterations, nbhd size=3, neg = 0 0462: dt=1.503650, rms=0.497 (0.096%), neg=0, invalid=96777 iter 0, gcam->neg = 75 after 200 iterations, nbhd size=3, neg = 3 starting rms=0.005, neg=3, removing folds in lattice.... iter 1, dt=0.000031: new neg 2, old_neg 3, delta 1, rms=0.005 (14.613%) iter 2, dt=0.000031: new neg 1, old_neg 2, delta 1, rms=0.004 (5.261%) iter 3, dt=0.000036: new neg 0, old_neg 1, delta 1, rms=0.004 (4.955%) 0463: dt=1.691489, rms=0.496 (0.132%), neg=0, invalid=96777 iter 0, gcam->neg = 6 after 12 iterations, nbhd size=1, neg = 0 0464: dt=0.714286, rms=0.496 (0.032%), neg=0, invalid=96777 iter 0, gcam->neg = 41 after 200 iterations, nbhd size=4, neg = 10 starting rms=0.005, neg=10, removing folds in lattice.... iter 1, dt=0.000039: new neg 1, old_neg 10, delta 9, rms=0.004 (22.608%) iter 2, dt=0.000036: new neg 0, old_neg 1, delta 1, rms=0.003 (6.170%) 0465: dt=0.714286, rms=0.496 (0.046%), neg=0, invalid=96777 iter 0, gcam->neg = 9 after 33 iterations, nbhd size=4, neg = 0 0466: dt=0.714286, rms=0.495 (0.041%), neg=0, invalid=96777 iter 0, gcam->neg = 6 after 200 iterations, nbhd size=4, neg = 1 starting rms=0.004, neg=1, removing folds in lattice.... iter 1, dt=0.000047: new neg 0, old_neg 1, delta 1, rms=0.003 (9.972%) 0467: dt=0.714286, rms=0.495 (0.083%), neg=0, invalid=96777 iter 0, gcam->neg = 1 after 0 iterations, nbhd size=0, neg = 0 0468: dt=0.714286, rms=0.495 (0.037%), neg=0, invalid=96777 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.495, neg=0, invalid=96777 iter 0, gcam->neg = 153 after 200 iterations, nbhd size=2, neg = 7 starting rms=0.005, neg=7, removing folds in lattice.... iter 1, dt=0.000039: new neg 2, old_neg 7, delta 5, rms=0.004 (25.711%) iter 2, dt=0.000082: new neg 2, old_neg 2, delta 0, rms=0.004 (8.081%) iter 3, dt=0.000036: new neg 0, old_neg 2, delta 2, rms=0.004 (4.499%) 0469: dt=3.189189, rms=0.494 (0.173%), neg=0, invalid=96777 iter 0, gcam->neg = 2 after 0 iterations, nbhd size=0, neg = 0 0470: dt=0.700000, rms=0.494 (0.025%), neg=0, invalid=96777 0471: dt=0.700000, rms=0.494 (0.048%), neg=0, invalid=96777 iter 0, gcam->neg = 59 after 200 iterations, nbhd size=1, neg = 11 starting rms=0.005, neg=11, removing folds in lattice.... iter 1, dt=0.000047: new neg 4, old_neg 11, delta 7, rms=0.004 (20.406%) iter 2, dt=0.000036: new neg 2, old_neg 4, delta 2, rms=0.004 (6.189%) iter 3, dt=0.000082: new neg 2, old_neg 2, delta 0, rms=0.004 (4.302%) iter 4, dt=0.000036: new neg 1, old_neg 2, delta 1, rms=0.003 (3.429%) iter 5, dt=0.000123: new neg 2, old_neg 1, delta -1, rms=0.003 (2.665%) iter 6, dt=0.000036: new neg 0, old_neg 2, delta 2, rms=0.003 (2.810%) 0472: dt=0.700000, rms=0.493 (0.080%), neg=0, invalid=96777 iter 0, gcam->neg = 8 after 10 iterations, nbhd size=1, neg = 0 0473: dt=0.700000, rms=0.493 (0.027%), neg=0, invalid=96777 iter 0, gcam->neg = 7 after 8 iterations, nbhd size=1, neg = 0 0474: dt=0.700000, rms=0.493 (0.069%), neg=0, invalid=96777 iter 0, gcam->neg = 2 after 8 iterations, nbhd size=1, neg = 0 0475: dt=0.700000, rms=0.492 (0.102%), neg=0, invalid=96777 iter 0, gcam->neg = 6 after 200 iterations, nbhd size=4, neg = 2 starting rms=0.003, neg=2, removing folds in lattice.... iter 1, dt=0.000031: new neg 0, old_neg 2, delta 2, rms=0.003 (12.381%) 0476: dt=0.700000, rms=0.492 (0.113%), neg=0, invalid=96777 iter 0, gcam->neg = 3 after 200 iterations, nbhd size=4, neg = 2 starting rms=0.003, neg=2, removing folds in lattice.... iter 1, dt=0.000031: new neg 1, old_neg 2, delta 1, rms=0.003 (13.789%) iter 2, dt=0.000036: new neg 0, old_neg 1, delta 1, rms=0.003 (3.037%) 0477: dt=0.700000, rms=0.491 (0.033%), neg=0, invalid=96777 setting smoothness coefficient to 0.400 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.492, neg=0, invalid=96777 iter 0, gcam->neg = 64 after 18 iterations, nbhd size=1, neg = 0 0478: dt=0.448980, rms=0.491 (0.117%), neg=0, invalid=96777 iter 0, gcam->neg = 43 after 13 iterations, nbhd size=1, neg = 0 0479: dt=0.216000, rms=0.491 (0.059%), neg=0, invalid=96777 iter 0, gcam->neg = 148 after 17 iterations, nbhd size=1, neg = 0 0480: dt=0.216000, rms=0.491 (0.046%), neg=0, invalid=96777 iter 0, gcam->neg = 110 after 23 iterations, nbhd size=1, neg = 0 0481: dt=0.216000, rms=0.490 (0.094%), neg=0, invalid=96777 iter 0, gcam->neg = 115 after 200 iterations, nbhd size=4, neg = 1 starting rms=0.006, neg=1, removing folds in lattice.... iter 1, dt=0.000072: new neg 1, old_neg 1, delta 0, rms=0.005 (22.176%) iter 2, dt=0.000102: new neg 1, old_neg 1, delta 0, rms=0.004 (11.854%) iter 3, dt=0.000143: new neg 0, old_neg 1, delta 1, rms=0.004 (7.872%) 0482: dt=0.216000, rms=0.490 (0.131%), neg=0, invalid=96777 iter 0, gcam->neg = 28 after 10 iterations, nbhd size=1, neg = 0 0483: dt=0.216000, rms=0.490 (0.046%), neg=0, invalid=96777 iter 0, gcam->neg = 69 after 13 iterations, nbhd size=1, neg = 0 0484: dt=0.216000, rms=0.489 (0.089%), neg=0, invalid=96777 iter 0, gcam->neg = 73 after 14 iterations, nbhd size=1, neg = 0 0485: dt=0.216000, rms=0.488 (0.129%), neg=0, invalid=96777 iter 0, gcam->neg = 138 after 13 iterations, nbhd size=1, neg = 0 0486: dt=0.216000, rms=0.488 (0.158%), neg=0, invalid=96777 iter 0, gcam->neg = 142 after 22 iterations, nbhd size=1, neg = 0 0487: dt=0.216000, rms=0.487 (0.165%), neg=0, invalid=96777 iter 0, gcam->neg = 249 after 41 iterations, nbhd size=2, neg = 0 0488: dt=0.216000, rms=0.486 (0.172%), neg=0, invalid=96777 iter 0, gcam->neg = 281 after 200 iterations, nbhd size=4, neg = 1 starting rms=0.007, neg=1, removing folds in lattice.... iter 1, dt=0.000055: new neg 0, old_neg 1, delta 1, rms=0.006 (18.374%) 0489: dt=0.216000, rms=0.485 (0.111%), neg=0, invalid=96777 iter 0, gcam->neg = 293 after 200 iterations, nbhd size=2, neg = 1 starting rms=0.006, neg=1, removing folds in lattice.... iter 1, dt=0.000055: new neg 1, old_neg 1, delta 0, rms=0.005 (19.248%) iter 2, dt=0.000098: new neg 0, old_neg 1, delta 1, rms=0.004 (9.473%) 0490: dt=0.216000, rms=0.485 (0.032%), neg=0, invalid=96777 iter 0, gcam->neg = 3 after 0 iterations, nbhd size=0, neg = 0 0491: dt=0.063000, rms=0.485 (0.010%), neg=0, invalid=96777 0492: dt=0.063000, rms=0.485 (0.013%), neg=0, invalid=96777 0493: dt=0.063000, rms=0.485 (0.022%), neg=0, invalid=96777 0494: dt=0.063000, rms=0.485 (0.031%), neg=0, invalid=96777 0495: dt=0.063000, rms=0.485 (0.041%), neg=0, invalid=96777 0496: dt=0.063000, rms=0.485 (0.048%), neg=0, invalid=96777 iter 0, gcam->neg = 1 after 1 iterations, nbhd size=0, neg = 0 0497: dt=0.063000, rms=0.484 (0.049%), neg=0, invalid=96777 iter 0, gcam->neg = 1 after 5 iterations, nbhd size=1, neg = 0 0498: dt=0.063000, rms=0.484 (0.058%), neg=0, invalid=96777 iter 0, gcam->neg = 1 after 5 iterations, nbhd size=1, neg = 0 0499: dt=0.063000, rms=0.484 (0.059%), neg=0, invalid=96777 iter 0, gcam->neg = 2 after 2 iterations, nbhd size=0, neg = 0 0500: dt=0.063000, rms=0.483 (0.064%), neg=0, invalid=96777 0501: dt=0.063000, rms=0.483 (0.061%), neg=0, invalid=96777 0502: dt=0.063000, rms=0.483 (0.070%), neg=0, invalid=96777 0503: dt=0.063000, rms=0.482 (0.067%), neg=0, invalid=96777 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.482, neg=0, invalid=96777 iter 0, gcam->neg = 92 after 15 iterations, nbhd size=1, neg = 0 0504: dt=0.566667, rms=0.482 (0.073%), neg=0, invalid=96777 iter 0, gcam->neg = 4 after 0 iterations, nbhd size=0, neg = 0 0505: dt=0.063000, rms=0.482 (0.011%), neg=0, invalid=96777 iter 0, gcam->neg = 2 after 1 iterations, nbhd size=0, neg = 0 0506: dt=0.063000, rms=0.482 (0.010%), neg=0, invalid=96777 iter 0, gcam->neg = 1 after 0 iterations, nbhd size=0, neg = 0 0507: dt=0.063000, rms=0.482 (0.023%), neg=0, invalid=96777 iter 0, gcam->neg = 3 after 2 iterations, nbhd size=0, neg = 0 0508: dt=0.063000, rms=0.482 (0.028%), neg=0, invalid=96777 iter 0, gcam->neg = 1 after 2 iterations, nbhd size=0, neg = 0 0509: dt=0.063000, rms=0.482 (0.037%), neg=0, invalid=96777 0510: dt=0.063000, rms=0.481 (0.046%), neg=0, invalid=96777 0511: dt=0.063000, rms=0.481 (0.050%), neg=0, invalid=96777 0512: dt=0.063000, rms=0.481 (0.055%), neg=0, invalid=96777 0513: dt=0.063000, rms=0.481 (0.057%), neg=0, invalid=96777 0514: dt=0.063000, rms=0.480 (0.064%), neg=0, invalid=96777 iter 0, gcam->neg = 1 after 2 iterations, nbhd size=0, neg = 0 0515: dt=0.063000, rms=0.480 (0.065%), neg=0, invalid=96777 0516: dt=0.063000, rms=0.480 (0.069%), neg=0, invalid=96777 0517: dt=0.063000, rms=0.479 (0.069%), neg=0, invalid=96777 0518: dt=0.063000, rms=0.479 (0.071%), neg=0, invalid=96777 0519: dt=0.063000, rms=0.479 (0.071%), neg=0, invalid=96777 0520: dt=0.063000, rms=0.478 (0.073%), neg=0, invalid=96777 0521: dt=0.063000, rms=0.478 (0.073%), neg=0, invalid=96777 setting smoothness coefficient to 1.000 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.481, neg=0, invalid=96777 0522: dt=0.000000, rms=0.481 (-0.000%), neg=0, invalid=96777 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.481, neg=0, invalid=96777 iter 0, gcam->neg = 14 after 11 iterations, nbhd size=1, neg = 0 0523: dt=0.112000, rms=0.480 (0.017%), neg=0, invalid=96777 0524: dt=0.007000, rms=0.480 (0.005%), neg=0, invalid=96777 iter 0, gcam->neg = 1 after 0 iterations, nbhd size=0, neg = 0 0525: dt=0.007000, rms=0.480 (0.002%), neg=0, invalid=96777 0526: dt=0.007000, rms=0.480 (0.001%), neg=0, invalid=96777 0527: dt=0.007000, rms=0.480 (0.005%), neg=0, invalid=96777 iter 0, gcam->neg = 1 after 0 iterations, nbhd size=0, neg = 0 0528: dt=0.007000, rms=0.480 (0.006%), neg=0, invalid=96777 iter 0, gcam->neg = 1 after 12 iterations, nbhd size=2, neg = 0 0529: dt=0.007000, rms=0.480 (0.002%), neg=0, invalid=96777 resetting metric properties... setting smoothness coefficient to 2.000 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.476, neg=0, invalid=96777 iter 0, gcam->neg = 488 after 40 iterations, nbhd size=3, neg = 0 0530: dt=0.308166, rms=0.468 (1.711%), neg=0, invalid=96777 0531: dt=0.000250, rms=0.468 (-0.001%), neg=0, invalid=96777 0532: dt=0.000250, rms=0.468 (0.003%), neg=0, invalid=96777 iter 0, gcam->neg = 2 after 8 iterations, nbhd size=1, neg = 0 0533: dt=0.000250, rms=0.468 (0.001%), neg=0, invalid=96777 iter 0, gcam->neg = 3 after 1 iterations, nbhd size=0, neg = 0 0534: dt=0.000250, rms=0.468 (0.001%), neg=0, invalid=96777 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.468, neg=0, invalid=96777 iter 0, gcam->neg = 1 after 1 iterations, nbhd size=0, neg = 0 0535: dt=0.000438, rms=0.468 (0.002%), neg=0, invalid=96777 iter 0, gcam->neg = 2 after 6 iterations, nbhd size=1, neg = 0 0536: dt=0.001750, rms=0.468 (0.008%), neg=0, invalid=96777 iter 0, gcam->neg = 172 after 35 iterations, nbhd size=3, neg = 0 0537: dt=0.112000, rms=0.466 (0.495%), neg=0, invalid=96777 0538: dt=0.000109, rms=0.466 (0.003%), neg=0, invalid=96777 0539: dt=0.000109, rms=0.466 (0.001%), neg=0, invalid=96777 0540: dt=0.000109, rms=0.466 (0.001%), neg=0, invalid=96777 0541: dt=0.000109, rms=0.465 (0.001%), neg=0, invalid=96777 0542: dt=0.000109, rms=0.465 (0.001%), neg=0, invalid=96777 0543: dt=0.000109, rms=0.465 (0.002%), neg=0, invalid=96777 0544: dt=0.000109, rms=0.465 (0.002%), neg=0, invalid=96777 0545: dt=0.000109, rms=0.465 (0.002%), neg=0, invalid=96777 0546: dt=0.000109, rms=0.465 (0.002%), neg=0, invalid=96777 0547: dt=0.000109, rms=0.465 (0.003%), neg=0, invalid=96777 0548: dt=0.000109, rms=0.465 (0.002%), neg=0, invalid=96777 iter 0, gcam->neg = 7 after 7 iterations, nbhd size=1, neg = 0 0549: dt=0.005000, rms=0.465 (0.018%), neg=0, invalid=96777 iter 0, gcam->neg = 10 after 6 iterations, nbhd size=1, neg = 0 0550: dt=0.006000, rms=0.465 (0.021%), neg=0, invalid=96777 iter 0, gcam->neg = 4 after 6 iterations, nbhd size=1, neg = 0 0551: dt=0.001750, rms=0.465 (0.005%), neg=0, invalid=96777 label assignment complete, 0 changed (0.00%) label assignment complete, 0 changed (0.00%) ***************** morphing with label term set to 0 ******************************* **************** pass 1 of 1 ************************ setting smoothness coefficient to 0.008 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.465, neg=0, invalid=96777 iter 0, gcam->neg = 2 after 200 iterations, nbhd size=4, neg = 4 starting rms=0.006, neg=4, removing folds in lattice.... iter 1, dt=0.000000: new neg 4, old_neg 4, delta 0, rms=0.006 (0.000%) ---------- unfolding failed - restoring original position -------------------- 0552: dt=8.092000, rms=0.465 (-0.078%), neg=0, invalid=96777 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.465, neg=0, invalid=96777 iter 0, gcam->neg = 2 after 200 iterations, nbhd size=4, neg = 6 starting rms=0.009, neg=6, removing folds in lattice.... iter 1, dt=0.000000: new neg 6, old_neg 6, delta 0, rms=0.009 (-0.000%) ---------- unfolding failed - restoring original position -------------------- 0553: dt=23.120000, rms=0.465 (0.000%), neg=0, invalid=96777 setting smoothness coefficient to 0.031 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.465, neg=0, invalid=96777 iter 0, gcam->neg = 1 after 200 iterations, nbhd size=1, neg = 3 starting rms=0.005, neg=3, removing folds in lattice.... iter 1, dt=0.000000: new neg 3, old_neg 3, delta 0, rms=0.005 (-0.000%) ---------- unfolding failed - restoring original position -------------------- 0554: dt=2.268000, rms=0.465 (0.000%), neg=0, invalid=96777 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.465, neg=0, invalid=96777 iter 0, gcam->neg = 12 after 200 iterations, nbhd size=3, neg = 7 starting rms=0.011, neg=7, removing folds in lattice.... iter 1, dt=0.000000: new neg 7, old_neg 7, delta 0, rms=0.011 (0.000%) ---------- unfolding failed - restoring original position -------------------- 0555: dt=7.776000, rms=0.465 (0.000%), neg=0, invalid=96777 setting smoothness coefficient to 0.118 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.465, neg=0, invalid=96777 iter 0, gcam->neg = 20 after 124 iterations, nbhd size=4, neg = 0 0556: dt=1.534884, rms=0.465 (0.043%), neg=0, invalid=96777 iter 0, gcam->neg = 8 after 84 iterations, nbhd size=4, neg = 0 0557: dt=0.300000, rms=0.465 (0.005%), neg=0, invalid=96777 iter 0, gcam->neg = 12 after 200 iterations, nbhd size=3, neg = 1 starting rms=0.003, neg=1, removing folds in lattice.... iter 1, dt=0.000000: new neg 1, old_neg 1, delta 0, rms=0.003 (0.000%) ---------- unfolding failed - restoring original position -------------------- 0558: dt=0.300000, rms=0.465 (0.000%), neg=0, invalid=96777 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.465, neg=0, invalid=96777 iter 0, gcam->neg = 9 after 200 iterations, nbhd size=2, neg = 1 starting rms=0.004, neg=1, removing folds in lattice.... iter 1, dt=0.000000: new neg 1, old_neg 1, delta 0, rms=0.004 (-0.000%) ---------- unfolding failed - restoring original position -------------------- 0559: dt=0.600000, rms=0.465 (0.000%), neg=0, invalid=96777 setting smoothness coefficient to 0.400 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.465, neg=0, invalid=96777 iter 0, gcam->neg = 23 after 200 iterations, nbhd size=3, neg = 1 starting rms=0.003, neg=1, removing folds in lattice.... iter 1, dt=0.000000: new neg 1, old_neg 1, delta 0, rms=0.003 (0.000%) ---------- unfolding failed - restoring original position -------------------- 0560: dt=0.144000, rms=0.465 (0.000%), neg=0, invalid=96777 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.465, neg=0, invalid=96777 iter 0, gcam->neg = 41 after 200 iterations, nbhd size=2, neg = 1 starting rms=0.003, neg=1, removing folds in lattice.... iter 1, dt=0.000000: new neg 1, old_neg 1, delta 0, rms=0.003 (0.000%) ---------- unfolding failed - restoring original position -------------------- 0561: dt=0.252000, rms=0.465 (0.000%), neg=0, invalid=96777 setting smoothness coefficient to 1.000 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.465, neg=0, invalid=96777 iter 0, gcam->neg = 28 after 22 iterations, nbhd size=2, neg = 0 0562: dt=0.028000, rms=0.465 (0.024%), neg=0, invalid=96777 iter 0, gcam->neg = 12 after 22 iterations, nbhd size=2, neg = 0 0563: dt=0.028000, rms=0.465 (0.025%), neg=0, invalid=96777 iter 0, gcam->neg = 8 after 31 iterations, nbhd size=4, neg = 0 0564: dt=0.028000, rms=0.465 (0.025%), neg=0, invalid=96777 iter 0, gcam->neg = 10 after 35 iterations, nbhd size=4, neg = 0 0565: dt=0.028000, rms=0.465 (0.025%), neg=0, invalid=96777 iter 0, gcam->neg = 13 after 20 iterations, nbhd size=2, neg = 0 0566: dt=0.028000, rms=0.464 (0.025%), neg=0, invalid=96777 iter 0, gcam->neg = 23 after 43 iterations, nbhd size=1, neg = 0 0567: dt=0.028000, rms=0.464 (0.044%), neg=0, invalid=96777 iter 0, gcam->neg = 21 after 45 iterations, nbhd size=1, neg = 0 0568: dt=0.028000, rms=0.464 (0.065%), neg=0, invalid=96777 iter 0, gcam->neg = 24 after 62 iterations, nbhd size=1, neg = 0 0569: dt=0.028000, rms=0.464 (0.044%), neg=0, invalid=96777 iter 0, gcam->neg = 41 after 53 iterations, nbhd size=1, neg = 0 0570: dt=0.028000, rms=0.463 (0.092%), neg=0, invalid=96777 iter 0, gcam->neg = 48 after 52 iterations, nbhd size=1, neg = 0 0571: dt=0.028000, rms=0.463 (0.096%), neg=0, invalid=96777 iter 0, gcam->neg = 74 after 53 iterations, nbhd size=1, neg = 0 0572: dt=0.028000, rms=0.462 (0.079%), neg=0, invalid=96777 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.462, neg=0, invalid=96777 iter 0, gcam->neg = 9 after 9 iterations, nbhd size=1, neg = 0 0573: dt=0.016000, rms=0.462 (0.017%), neg=0, invalid=96777 iter 0, gcam->neg = 13 after 200 iterations, nbhd size=2, neg = 1 starting rms=0.003, neg=1, removing folds in lattice.... iter 1, dt=0.000000: new neg 1, old_neg 1, delta 0, rms=0.003 (0.000%) ---------- unfolding failed - restoring original position -------------------- 0574: dt=0.028000, rms=0.462 (0.000%), neg=0, invalid=96777 resetting metric properties... setting smoothness coefficient to 2.000 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.462, neg=0, invalid=96777 iter 0, gcam->neg = 143 after 200 iterations, nbhd size=1, neg = 1 starting rms=0.003, neg=1, removing folds in lattice.... iter 1, dt=0.000000: new neg 1, old_neg 1, delta 0, rms=0.003 (0.000%) ---------- unfolding failed - restoring original position -------------------- 0575: dt=0.078179, rms=0.462 (0.000%), neg=0, invalid=96777 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.462, neg=0, invalid=96777 iter 0, gcam->neg = 216 after 200 iterations, nbhd size=1, neg = 1 starting rms=0.010, neg=1, removing folds in lattice.... iter 1, dt=0.000000: new neg 1, old_neg 1, delta 0, rms=0.010 (-0.000%) ---------- unfolding failed - restoring original position -------------------- 0576: dt=0.096000, rms=0.462 (0.000%), neg=0, invalid=96777 writing output transformation to transforms/talairach.m3z... GCAMwrite registration took 21 hours, 49 minutes and 40 seconds. #-------------------------------------- #@# CA Reg Inv Sat Feb 17 13:31:17 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri mri_ca_register -invert-and-save transforms/talairach.m3z Loading, Inverting, Saving, Exiting ... Reading transforms/talairach.m3z Inverting GCAM Saving inverse #-------------------------------------- #@# Remove Neck Sat Feb 17 13:33:07 PST 2018 mri_remove_neck -radius 25 nu.mgz transforms/talairach.m3z /usr/local/freesurfer/average/RB_all_2008-03-26.gca nu_noneck.mgz erasing everything more than 25 mm from possible brain reading atlas '/usr/local/freesurfer/average/RB_all_2008-03-26.gca'... reading input volume 'nu.mgz'... reading transform 'transforms/talairach.m3z'... removing structures at least 25 mm from brain... 11316242 nonbrain voxels erased writing output to nu_noneck.mgz... nonbrain removal took 2 minutes and 1 seconds. #-------------------------------------- #@# SkullLTA Sat Feb 17 13:35:08 PST 2018 mri_em_register -skull -t transforms/talairach.lta nu_noneck.mgz /usr/local/freesurfer/average/RB_all_withskull_2008-03-26.gca transforms/talairach_with_skull_2.lta aligning to atlas containing skull, setting unknown_nbr_spacing = 5 using previously computed transform transforms/talairach.lta reading 1 input volumes... logging results to talairach_with_skull_2.log reading '/usr/local/freesurfer/average/RB_all_withskull_2008-03-26.gca'... average std = 23.1 using min determinant for regularization = 53.4 0 singular and 5702 ill-conditioned covariance matrices regularized reading 'nu_noneck.mgz'... freeing gibbs priors...done. bounding unknown intensity as < 20.2 or > 943.7 total sample mean = 92.0 (1443 zeros) ************************************************ spacing=8, using 3481 sample points, tol=1.00e-05... ************************************************ register_mri: find_optimal_transform find_optimal_transform: nsamples 3481, passno 0, spacing 8 resetting wm mean[0]: 117 --> 126 resetting gm mean[0]: 74 --> 74 input volume #1 is the most T1-like using real data threshold=12.0 skull bounding box = (42, 51, 19) --> (209, 222, 237) using (98, 108, 128) as brain centroid... mean wm in atlas = 126, using box (77,87,101) --> (118, 129,154) to find MRI wm before smoothing, mri peak at 133 after smoothing, mri peak at 132, scaling input intensities by 0.955 scaling channel 0 by 0.954545 **************************************** Nine parameter search. iteration 0 nscales = 0 ... **************************************** Result so far: scale 1.000: max_log_p=-4.2, old_max_log_p =-4.4 (thresh=-4.4) 1.084 -0.011 0.010 -13.102; 0.010 1.446 -0.031 -77.798; -0.008 0.028 1.003 -22.045; 0.000 0.000 0.000 1.000; **************************************** Nine parameter search. iteration 1 nscales = 0 ... **************************************** Result so far: scale 1.000: max_log_p=-4.2, old_max_log_p =-4.2 (thresh=-4.2) 1.084 -0.011 0.010 -13.102; 0.010 1.430 -0.162 -59.378; -0.006 0.217 0.991 -46.912; 0.000 0.000 0.000 1.000; **************************************** Nine parameter search. iteration 2 nscales = 0 ... **************************************** Result so far: scale 1.000: max_log_p=-4.2, old_max_log_p =-4.2 (thresh=-4.2) 1.084 -0.011 0.010 -13.102; 0.010 1.430 -0.162 -59.378; -0.006 0.217 0.991 -46.912; 0.000 0.000 0.000 1.000; reducing scale to 0.2500 **************************************** Nine parameter search. iteration 3 nscales = 1 ... **************************************** Result so far: scale 0.250: max_log_p=-4.1, old_max_log_p =-4.2 (thresh=-4.2) 1.022 0.079 0.007 -17.394; -0.060 1.417 -0.031 -66.543; -0.008 0.029 1.021 -24.357; 0.000 0.000 0.000 1.000; **************************************** Nine parameter search. iteration 4 nscales = 1 ... **************************************** Result so far: scale 0.250: max_log_p=-4.1, old_max_log_p =-4.1 (thresh=-4.1) 1.022 0.079 0.007 -15.519; -0.059 1.390 -0.030 -64.900; -0.008 0.029 1.040 -28.677; 0.000 0.000 0.000 1.000; **************************************** Nine parameter search. iteration 5 nscales = 1 ... **************************************** Result so far: scale 0.250: max_log_p=-4.1, old_max_log_p =-4.1 (thresh=-4.1) 1.022 0.079 0.007 -15.519; -0.059 1.390 -0.030 -64.900; -0.008 0.029 1.040 -28.677; 0.000 0.000 0.000 1.000; reducing scale to 0.0625 **************************************** Nine parameter search. iteration 6 nscales = 2 ... **************************************** Result so far: scale 0.062: max_log_p=-4.1, old_max_log_p =-4.1 (thresh=-4.1) 1.022 0.125 -0.002 -21.245; -0.093 1.388 -0.030 -60.911; 0.000 0.030 1.038 -29.011; 0.000 0.000 0.000 1.000; **************************************** Nine parameter search. iteration 7 nscales = 2 ... **************************************** Result so far: scale 0.062: max_log_p=-4.1, old_max_log_p =-4.1 (thresh=-4.1) 1.022 0.102 -0.002 -18.078; -0.076 1.390 -0.030 -63.292; 0.000 0.029 1.034 -28.536; 0.000 0.000 0.000 1.000; min search scale 0.025000 reached *********************************************** Computing MAP estimate using 3481 samples... *********************************************** dt = 5.00e-06, momentum=0.80, tol=1.00e-05 l_intensity = 1.0000 Aligning input volume to GCA... Transform matrix 1.02183 0.10183 -0.00185 -18.07829; -0.07586 1.39028 -0.03022 -63.29237; 0.00032 0.02950 1.03438 -28.53612; 0.00000 0.00000 0.00000 1.00000; nsamples 3481 Quasinewton: input matrix 1.02183 0.10183 -0.00185 -18.07829; -0.07586 1.39028 -0.03022 -63.29237; 0.00032 0.02950 1.03438 -28.53612; 0.00000 0.00000 0.00000 1.00000; IFLAG= -1 LINE SEARCH FAILED. SEE DOCUMENTATION OF ROUTINE MCSRCH ERROR RETURN OF LINE SEARCH: INFO= 3 POSSIBLE CAUSES: FUNCTION OR GRADIENT ARE INCORRECT OR INCORRECT TOLERANCESoutof QuasiNewtonEMA: 009: -log(p) = -0.0 tol 0.000010 Resulting transform: 1.022 0.102 -0.002 -18.078; -0.076 1.390 -0.030 -63.292; 0.000 0.029 1.034 -28.536; 0.000 0.000 0.000 1.000; pass 1, spacing 8: log(p) = -4.1 (old=-4.4) transform before final EM align: 1.022 0.102 -0.002 -18.078; -0.076 1.390 -0.030 -63.292; 0.000 0.029 1.034 -28.536; 0.000 0.000 0.000 1.000; ************************************************** EM alignment process ... Computing final MAP estimate using 382743 samples. ************************************************** dt = 5.00e-06, momentum=0.80, tol=1.00e-07 l_intensity = 1.0000 Aligning input volume to GCA... Transform matrix 1.02183 0.10183 -0.00185 -18.07829; -0.07586 1.39028 -0.03022 -63.29237; 0.00032 0.02950 1.03438 -28.53612; 0.00000 0.00000 0.00000 1.00000; nsamples 382743 Quasinewton: input matrix 1.02183 0.10183 -0.00185 -18.07829; -0.07586 1.39028 -0.03022 -63.29237; 0.00032 0.02950 1.03438 -28.53612; 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) = 4.5 tol 0.000000 final transform: 1.022 0.102 -0.002 -18.078; -0.076 1.390 -0.030 -63.292; 0.000 0.029 1.034 -28.536; 0.000 0.000 0.000 1.000; writing output transformation to transforms/talairach_with_skull_2.lta... registration took 45 minutes and 15 seconds. #-------------------------------------- #@# SubCort Seg Sat Feb 17 14:20:23 PST 2018 mri_ca_label -align norm.mgz transforms/talairach.m3z /usr/local/freesurfer/average/RB_all_2008-03-26.gca aseg.auto_noCCseg.mgz sysname Linux hostname induction.sdsc.edu machine x86_64 setenv SUBJECTS_DIR /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w cd /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri mri_ca_label -align norm.mgz transforms/talairach.m3z /usr/local/freesurfer/average/RB_all_2008-03-26.gca aseg.auto_noCCseg.mgz renormalizing sequences with structure alignment, equivalent to: -renormalize -renormalize_mean 0.500 -regularize 0.500 reading 1 input volumes... reading classifier array from /usr/local/freesurfer/average/RB_all_2008-03-26.gca... reading input volume from norm.mgz... average std[0] = 6.9 reading transform from transforms/talairach.m3z... Atlas used for the 3D morph was /usr/local/freesurfer/average/RB_all_2008-03-26.gca average std = 6.9 using min determinant for regularization = 4.7 0 singular and 0 ill-conditioned covariance matrices regularized labeling volume... renormalizing by structure alignment.... renormalizing input #0 gca peak = 0.15151 (27) mri peak = 0.14731 (40) Left_Lateral_Ventricle (4): linear fit = 1.46 x + 0.0 (601 voxels, overlap=0.120) Left_Lateral_Ventricle (4): linear fit = 1.46 x + 0.0 (601 voxels, peak = 39), gca=39.3 gca peak = 0.14982 (20) mri peak = 0.14239 (36) Right_Lateral_Ventricle (43): linear fit = 1.58 x + 0.0 (488 voxels, overlap=0.089) Right_Lateral_Ventricle (43): linear fit = 1.50 x + 0.0 (488 voxels, peak = 32), gca=30.0 gca peak = 0.28003 (97) mri peak = 0.10108 (101) Right_Pallidum (52): linear fit = 1.00 x + 0.0 (271 voxels, overlap=1.026) Right_Pallidum (52): linear fit = 1.00 x + 0.0 (271 voxels, peak = 97), gca=97.5 gca peak = 0.18160 (96) mri peak = 0.10596 (94) Left_Pallidum (13): linear fit = 0.96 x + 0.0 (238 voxels, overlap=1.010) Left_Pallidum (13): linear fit = 0.96 x + 0.0 (238 voxels, peak = 93), gca=92.6 gca peak = 0.27536 (62) mri peak = 0.09302 (78) Right_Hippocampus (53): linear fit = 1.24 x + 0.0 (386 voxels, overlap=0.021) Right_Hippocampus (53): linear fit = 1.24 x + 0.0 (386 voxels, peak = 77), gca=76.6 gca peak = 0.32745 (63) mri peak = 0.08967 (82) Left_Hippocampus (17): linear fit = 1.22 x + 0.0 (511 voxels, overlap=0.028) Left_Hippocampus (17): linear fit = 1.22 x + 0.0 (511 voxels, peak = 77), gca=76.5 gca peak = 0.08597 (105) mri peak = 0.08499 (107) Right_Cerebral_White_Matter (41): linear fit = 1.00 x + 0.0 (52840 voxels, overlap=0.776) Right_Cerebral_White_Matter (41): linear fit = 1.00 x + 0.0 (52840 voxels, peak = 106), gca=105.5 gca peak = 0.09209 (106) mri peak = 0.08002 (107) Left_Cerebral_White_Matter (2): linear fit = 1.00 x + 0.0 (52591 voxels, overlap=0.779) Left_Cerebral_White_Matter (2): linear fit = 1.00 x + 0.0 (52591 voxels, peak = 106), gca=106.0 gca peak = 0.07826 (63) mri peak = 0.05150 (74) Left_Cerebral_Cortex (3): linear fit = 1.23 x + 0.0 (18338 voxels, overlap=0.194) Left_Cerebral_Cortex (3): linear fit = 1.23 x + 0.0 (18338 voxels, peak = 77), gca=77.2 gca peak = 0.08598 (64) mri peak = 0.05442 (78) Right_Cerebral_Cortex (42): linear fit = 1.23 x + 0.0 (17349 voxels, overlap=0.212) Right_Cerebral_Cortex (42): linear fit = 1.23 x + 0.0 (17349 voxels, peak = 78), gca=78.4 gca peak = 0.24164 (71) mri peak = 0.10405 (84) Right_Caudate (50): linear fit = 1.15 x + 0.0 (428 voxels, overlap=0.020) Right_Caudate (50): linear fit = 1.15 x + 0.0 (428 voxels, peak = 82), gca=82.0 gca peak = 0.18227 (75) mri peak = 0.10677 (84) Left_Caudate (11): linear fit = 1.11 x + 0.0 (516 voxels, overlap=0.542) Left_Caudate (11): linear fit = 1.11 x + 0.0 (516 voxels, peak = 83), gca=82.9 gca peak = 0.10629 (62) mri peak = 0.04491 (65) Left_Cerebellum_Cortex (8): linear fit = 1.22 x + 0.0 (598 voxels, overlap=0.491) Left_Cerebellum_Cortex (8): linear fit = 1.22 x + 0.0 (598 voxels, peak = 75), gca=75.3 gca peak = 0.11668 (59) mri peak = 0.04825 (76) Right_Cerebellum_Cortex (47): linear fit = 1.25 x + 0.0 (408 voxels, overlap=0.199) Right_Cerebellum_Cortex (47): linear fit = 1.25 x + 0.0 (408 voxels, peak = 73), gca=73.5 gca peak = 0.17849 (88) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.16819 (86) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.41688 (64) mri peak = 0.11798 (79) Left_Amygdala (18): linear fit = 1.23 x + 0.0 (178 voxels, overlap=0.068) Left_Amygdala (18): linear fit = 1.23 x + 0.0 (178 voxels, peak = 78), gca=78.4 gca peak = 0.42394 (62) mri peak = 0.13085 (81) Right_Amygdala (54): linear fit = 1.26 x + 0.0 (211 voxels, overlap=0.064) Right_Amygdala (54): linear fit = 1.26 x + 0.0 (211 voxels, peak = 78), gca=78.4 gca peak = 0.10041 (96) mri peak = 0.08076 (100) Left_Thalamus_Proper (10): linear fit = 1.08 x + 0.0 (3799 voxels, overlap=0.715) Left_Thalamus_Proper (10): linear fit = 1.08 x + 0.0 (3799 voxels, peak = 103), gca=103.2 gca peak = 0.13978 (88) mri peak = 0.07539 (96) Right_Thalamus_Proper (49): linear fit = 1.09 x + 0.0 (3075 voxels, overlap=0.380) Right_Thalamus_Proper (49): linear fit = 1.09 x + 0.0 (3075 voxels, peak = 95), gca=95.5 gca peak = 0.08514 (81) mri peak = 0.07907 (88) Left_Putamen (12): linear fit = 1.05 x + 0.0 (1895 voxels, overlap=0.794) Left_Putamen (12): linear fit = 1.05 x + 0.0 (1895 voxels, peak = 85), gca=85.5 gca peak = 0.09624 (82) mri peak = 0.09049 (88) Right_Putamen (51): linear fit = 1.09 x + 0.0 (1746 voxels, overlap=0.586) Right_Putamen (51): linear fit = 1.09 x + 0.0 (1746 voxels, peak = 89), gca=89.0 gca peak = 0.07543 (88) mri peak = 0.09070 (103) Brain_Stem (16): linear fit = 1.16 x + 0.0 (1809 voxels, overlap=0.013) Brain_Stem (16): linear fit = 1.16 x + 0.0 (1809 voxels, peak = 103), gca=102.5 gca peak = 0.12757 (95) mri peak = 0.08188 (99) Right_VentralDC (60): linear fit = 1.08 x + 0.0 (595 voxels, overlap=0.397) Right_VentralDC (60): linear fit = 1.08 x + 0.0 (595 voxels, peak = 102), gca=102.1 gca peak = 0.17004 (92) mri peak = 0.09598 (101) Left_VentralDC (28): linear fit = 1.09 x + 0.0 (689 voxels, overlap=0.700) Left_VentralDC (28): linear fit = 1.09 x + 0.0 (689 voxels, peak = 100), gca=99.8 gca peak = 0.21361 (36) mri peak = 0.10264 (37) gca peak = 0.26069 (23) uniform distribution in MR - rejecting arbitrary fit gca peak Unknown = 0.94427 ( 0) gca peak Left_Inf_Lat_Vent = 0.31795 (35) gca peak Left_Cerebellum_White_Matter = 0.17849 (88) gca peak Third_Ventricle = 0.21361 (36) gca peak Fourth_Ventricle = 0.26069 (23) gca peak CSF = 0.14367 (38) gca peak Left_Accumbens_area = 0.57033 (70) gca peak Left_undetermined = 1.00000 (35) gca peak Left_vessel = 0.65201 (62) gca peak Left_choroid_plexus = 0.09084 (48) gca peak Right_Inf_Lat_Vent = 0.31129 (32) gca peak Right_Cerebellum_White_Matter = 0.16819 (86) gca peak Right_Accumbens_area = 0.30219 (72) gca peak Right_vessel = 0.83418 (60) gca peak Right_choroid_plexus = 0.10189 (48) gca peak Fifth_Ventricle = 0.72939 (42) gca peak WM_hypointensities = 0.14821 (82) gca peak non_WM_hypointensities = 0.10354 (53) gca peak Optic_Chiasm = 0.34849 (76) not using caudate to estimate GM means estimating mean gm scale to be 1.23 x + 0.0 estimating mean wm scale to be 1.00 x + 0.0 estimating mean csf scale to be 1.48 x + 0.0 saving intensity scales to aseg.auto_noCCseg.label_intensities.txt renormalizing by structure alignment.... renormalizing input #0 gca peak = 0.11429 (40) mri peak = 0.14731 (40) Left_Lateral_Ventricle (4): linear fit = 0.99 x + 0.0 (601 voxels, overlap=0.783) Left_Lateral_Ventricle (4): linear fit = 0.99 x + 0.0 (601 voxels, peak = 39), gca=39.4 gca peak = 0.12270 (30) mri peak = 0.14239 (36) Right_Lateral_Ventricle (43): linear fit = 1.12 x + 0.0 (488 voxels, overlap=0.619) Right_Lateral_Ventricle (43): linear fit = 1.12 x + 0.0 (488 voxels, peak = 33), gca=33.5 gca peak = 0.27791 (98) mri peak = 0.10108 (101) Right_Pallidum (52): linear fit = 1.00 x + 0.0 (271 voxels, overlap=1.023) Right_Pallidum (52): linear fit = 1.00 x + 0.0 (271 voxels, peak = 98), gca=98.5 gca peak = 0.20055 (92) mri peak = 0.10596 (94) Left_Pallidum (13): linear fit = 1.01 x + 0.0 (238 voxels, overlap=0.945) Left_Pallidum (13): linear fit = 1.01 x + 0.0 (238 voxels, peak = 93), gca=93.4 gca peak = 0.25386 (77) mri peak = 0.09302 (78) Right_Hippocampus (53): linear fit = 1.00 x + 0.0 (386 voxels, overlap=1.005) Right_Hippocampus (53): linear fit = 1.00 x + 0.0 (386 voxels, peak = 77), gca=77.0 gca peak = 0.24376 (77) mri peak = 0.08967 (82) Left_Hippocampus (17): linear fit = 1.00 x + 0.0 (511 voxels, overlap=1.003) Left_Hippocampus (17): linear fit = 1.00 x + 0.0 (511 voxels, peak = 77), gca=77.0 gca peak = 0.08547 (106) mri peak = 0.08499 (107) Right_Cerebral_White_Matter (41): linear fit = 1.00 x + 0.0 (52840 voxels, overlap=0.785) Right_Cerebral_White_Matter (41): linear fit = 1.00 x + 0.0 (52840 voxels, peak = 106), gca=106.0 gca peak = 0.09208 (106) mri peak = 0.08002 (107) Left_Cerebral_White_Matter (2): linear fit = 1.00 x + 0.0 (52591 voxels, overlap=0.779) Left_Cerebral_White_Matter (2): linear fit = 1.00 x + 0.0 (52591 voxels, peak = 106), gca=106.0 gca peak = 0.06429 (77) mri peak = 0.05150 (74) Left_Cerebral_Cortex (3): linear fit = 1.00 x + 0.0 (18338 voxels, overlap=0.882) Left_Cerebral_Cortex (3): linear fit = 1.00 x + 0.0 (18338 voxels, peak = 77), gca=77.0 gca peak = 0.07101 (77) mri peak = 0.05442 (78) Right_Cerebral_Cortex (42): linear fit = 0.99 x + 0.0 (17349 voxels, overlap=0.893) Right_Cerebral_Cortex (42): linear fit = 0.99 x + 0.0 (17349 voxels, peak = 76), gca=75.8 gca peak = 0.27182 (85) mri peak = 0.10405 (84) Right_Caudate (50): linear fit = 1.00 x + 0.0 (428 voxels, overlap=1.005) Right_Caudate (50): linear fit = 1.00 x + 0.0 (428 voxels, peak = 85), gca=85.0 gca peak = 0.18166 (83) mri peak = 0.10677 (84) Left_Caudate (11): linear fit = 1.00 x + 0.0 (516 voxels, overlap=0.830) Left_Caudate (11): linear fit = 1.00 x + 0.0 (516 voxels, peak = 83), gca=83.0 gca peak = 0.08578 (75) mri peak = 0.04491 (65) Left_Cerebellum_Cortex (8): linear fit = 0.98 x + 0.0 (598 voxels, overlap=0.938) Left_Cerebellum_Cortex (8): linear fit = 0.98 x + 0.0 (598 voxels, peak = 73), gca=73.1 gca peak = 0.10410 (74) mri peak = 0.04825 (76) Right_Cerebellum_Cortex (47): linear fit = 1.01 x + 0.0 (408 voxels, overlap=0.657) Right_Cerebellum_Cortex (47): linear fit = 1.01 x + 0.0 (408 voxels, peak = 75), gca=75.1 gca peak = 0.17257 (88) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.15116 (87) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.32588 (78) mri peak = 0.11798 (79) Left_Amygdala (18): linear fit = 1.02 x + 0.0 (178 voxels, overlap=1.018) Left_Amygdala (18): linear fit = 1.02 x + 0.0 (178 voxels, peak = 80), gca=79.9 gca peak = 0.33222 (79) mri peak = 0.13085 (81) Right_Amygdala (54): linear fit = 1.01 x + 0.0 (211 voxels, overlap=1.023) Right_Amygdala (54): linear fit = 1.01 x + 0.0 (211 voxels, peak = 80), gca=80.2 gca peak = 0.10447 (103) mri peak = 0.08076 (100) Left_Thalamus_Proper (10): linear fit = 0.99 x + 0.0 (3799 voxels, overlap=0.977) Left_Thalamus_Proper (10): linear fit = 0.99 x + 0.0 (3799 voxels, peak = 101), gca=101.5 gca peak = 0.11564 (95) mri peak = 0.07539 (96) Right_Thalamus_Proper (49): linear fit = 1.00 x + 0.0 (3075 voxels, overlap=0.913) Right_Thalamus_Proper (49): linear fit = 1.00 x + 0.0 (3075 voxels, peak = 95), gca=95.5 gca peak = 0.09630 (92) mri peak = 0.07907 (88) Left_Putamen (12): linear fit = 1.00 x + 0.0 (1895 voxels, overlap=0.954) Left_Putamen (12): linear fit = 1.00 x + 0.0 (1895 voxels, peak = 92), gca=91.5 gca peak = 0.10507 (82) mri peak = 0.09049 (88) Right_Putamen (51): linear fit = 1.00 x + 0.0 (1746 voxels, overlap=0.880) Right_Putamen (51): linear fit = 1.00 x + 0.0 (1746 voxels, peak = 82), gca=82.4 gca peak = 0.06344 (103) mri peak = 0.09070 (103) Brain_Stem (16): linear fit = 1.00 x + 0.0 (1809 voxels, overlap=0.669) Brain_Stem (16): linear fit = 1.00 x + 0.0 (1809 voxels, peak = 102), gca=102.5 gca peak = 0.13818 (102) mri peak = 0.08188 (99) Right_VentralDC (60): linear fit = 1.00 x + 0.0 (595 voxels, overlap=0.810) Right_VentralDC (60): linear fit = 1.00 x + 0.0 (595 voxels, peak = 103), gca=102.5 gca peak = 0.16052 (100) mri peak = 0.09598 (101) Left_VentralDC (28): linear fit = 1.00 x + 0.0 (689 voxels, overlap=0.891) Left_VentralDC (28): linear fit = 1.00 x + 0.0 (689 voxels, peak = 100), gca=100.0 gca peak = 0.14773 (54) mri peak = 0.10264 (37) gca peak = 0.14965 (33) uniform distribution in MR - rejecting arbitrary fit gca peak Unknown = 0.94427 ( 0) gca peak Left_Inf_Lat_Vent = 0.22588 (43) gca peak Left_Cerebellum_White_Matter = 0.17257 (88) gca peak Third_Ventricle = 0.14773 (54) gca peak Fourth_Ventricle = 0.14965 (33) gca peak CSF = 0.16873 (57) gca peak Left_Accumbens_area = 0.46083 (77) gca peak Left_undetermined = 0.95107 (45) gca peak Left_vessel = 0.63670 (62) gca peak Left_choroid_plexus = 0.11331 (48) gca peak Right_Inf_Lat_Vent = 0.24786 (39) gca peak Right_Cerebellum_White_Matter = 0.15116 (87) gca peak Right_Accumbens_area = 0.31027 (83) gca peak Right_vessel = 0.83418 (60) gca peak Right_choroid_plexus = 0.13294 (46) gca peak Fifth_Ventricle = 0.45827 (61) gca peak WM_hypointensities = 0.17587 (82) gca peak non_WM_hypointensities = 0.13024 (53) gca peak Optic_Chiasm = 0.34347 (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 1.05 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 39442 gm and wm labels changed (%27 to gray, %73 to white out of all changed labels) 353 hippocampal voxels changed. 1 amygdala voxels changed. pass 1: 87276 changed. image ll: -2.181, PF=1.000 pass 2: 14359 changed. image ll: -2.178, PF=1.000 pass 3: 4131 changed. writing labeled volume to aseg.auto_noCCseg.mgz... auto-labeling took 42 minutes and 0 seconds. mri_cc -aseg aseg.auto_noCCseg.mgz -o aseg.auto.mgz -lta /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/transforms/cc_up.lta hcptest8_1mm will read input aseg from aseg.auto_noCCseg.mgz writing aseg with cc labels to aseg.auto.mgz will write lta as /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/transforms/cc_up.lta reading aseg from /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/aseg.auto_noCCseg.mgz reading norm from /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/norm.mgz 50802 voxels in left wm, 34723 in right wm, xrange [124, 134] searching rotation angles z=[-7 7], y=[-6 8] searching scale 1 Z rot -7.2 searching scale 1 Z rot -6.9 searching scale 1 Z rot -6.7 searching scale 1 Z rot -6.4 searching scale 1 Z rot -6.2 searching scale 1 Z rot -5.9 searching scale 1 Z rot -5.7 searching scale 1 Z rot -5.4 searching scale 1 Z rot -5.2 searching scale 1 Z rot -4.9 searching scale 1 Z rot -4.7 searching scale 1 Z rot -4.4 searching scale 1 Z rot -4.2 searching scale 1 Z rot -3.9 searching scale 1 Z rot -3.7 searching scale 1 Z rot -3.4 searching scale 1 Z rot -3.2 searching scale 1 Z rot -2.9 searching scale 1 Z rot -2.7 searching scale 1 Z rot -2.4 searching scale 1 Z rot -2.2 searching scale 1 Z rot -1.9 searching scale 1 Z rot -1.7 searching scale 1 Z rot -1.4 searching scale 1 Z rot -1.2 searching scale 1 Z rot -0.9 searching scale 1 Z rot -0.7 searching scale 1 Z rot -0.4 searching scale 1 Z rot -0.2 searching scale 1 Z rot 0.1 searching scale 1 Z rot 0.3 searching scale 1 Z rot 0.6 searching scale 1 Z rot 0.8 searching scale 1 Z rot 1.1 searching scale 1 Z rot 1.3 searching scale 1 Z rot 1.6 searching scale 1 Z rot 1.8 searching scale 1 Z rot 2.1 searching scale 1 Z rot 2.3 searching scale 1 Z rot 2.6 searching scale 1 Z rot 2.8 searching scale 1 Z rot 3.1 searching scale 1 Z rot 3.3 searching scale 1 Z rot 3.6 searching scale 1 Z rot 3.8 searching scale 1 Z rot 4.1 searching scale 1 Z rot 4.3 searching scale 1 Z rot 4.6 searching scale 1 Z rot 4.8 searching scale 1 Z rot 5.1 searching scale 1 Z rot 5.3 searching scale 1 Z rot 5.6 searching scale 1 Z rot 5.8 searching scale 1 Z rot 6.1 searching scale 1 Z rot 6.3 searching scale 1 Z rot 6.6 global minimum found at slice 127.8, rotations (1.26, -0.17) final transformation (x=127.8, yr=1.258, zr=-0.173): 1.000 0.003 0.022 -2.826; -0.003 1.000 -0.000 1.395; -0.022 -0.000 1.000 8.834; 0.000 0.000 0.000 1.000; updating x range to be [125, 129] in xformed coordinates best xformed slice 128 cc center is found at 128 151 167 eigenvectors: -0.000 -0.001 1.000; 0.124 -0.992 -0.001; 0.992 0.124 0.000; error in mid anterior detected - correcting... error in mid anterior detected - correcting... writing aseg with callosum to /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/aseg.auto.mgz... corpus callosum matter segmentation took 1.4 minutes #-------------------------------------- #@# Merge ASeg Sat Feb 17 15:03:48 PST 2018 cp aseg.auto.mgz aseg.mgz #-------------------------------------------- #@# Intensity Normalization2 Sat Feb 17 15:03:49 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri mri_normalize -noconform brainmask.mgz brain.mgz not interpolating and embedding volume to be 256^3... reading from brainmask.mgz... normalizing image... talairach transform 1.005 -0.003 0.010 -0.175; 0.006 1.052 0.032 -2.250; -0.027 0.038 1.154 2.810; 0.000 0.000 0.000 1.000; processing without aseg, no1d=0 MRInormInit(): INFO: Modifying talairach volume c_(r,a,s) based on average_305 MRInormalize(): MRIsplineNormalize(): npeaks = 19 Starting OpenSpline(): npoints = 19 building Voronoi diagram... performing soap bubble smoothing, sigma = 8... Iterating 2 times --------------------------------- 3d normalization pass 1 of 2 white matter peak found at 111 white matter peak found at 110 gm peak at 82 (82), valley at 58 (58) 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 111 white matter peak found at 110 gm peak at 82 (82), valley at 58 (58) csf peak at 29, setting threshold to 64 building Voronoi diagram... performing soap bubble smoothing, sigma = 8... Done iterating --------------------------------- writing output to brain.mgz 3D bias adjustment took 3 minutes and 12 seconds. #-------------------------------------------- #@# Mask BFS Sat Feb 17 15:07:04 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri mri_mask -T 5 brain.mgz brainmask.mgz brain.finalsurfs.mgz threshold mask volume at 5 DoAbs = 0 Found 1423082 voxels in mask (pct= 8.48) Writing masked volume to brain.finalsurfs.mgz...done. #-------------------------------------------- #@# WM Segmentation Sat Feb 17 15:07:11 PST 2018 mri_segment brain.mgz wm.seg.mgz doing initial intensity segmentation... using local statistics to label ambiguous voxels... computing class statistics for intensity windows... WM (106.0): 105.9 +- 5.9 [80.0 --> 125.0] GM (79.0) : 78.5 +- 10.2 [30.0 --> 96.0] setting bottom of white matter range to 88.7 setting top of gray matter range to 99.0 doing initial intensity segmentation... using local statistics to label ambiguous voxels... using local geometry to label remaining ambiguous voxels... reclassifying voxels using Gaussian border classifier... removing voxels with positive offset direction... smoothing T1 volume with sigma = 0.250 removing 1-dimensional structures... 8568 sparsely connected voxels removed... thickening thin strands.... 20 segments, 3204 filled 211 bright non-wm voxels segmented. 5630 diagonally connected voxels added... white matter segmentation took 2.2 minutes writing output to wm.seg.mgz... mri_pretess wm.seg.mgz wm brain.mgz wm.mgz Iteration Number : 1 pass 1 (xy+): 13 found - 13 modified | TOTAL: 13 pass 2 (xy+): 0 found - 13 modified | TOTAL: 13 pass 1 (xy-): 9 found - 9 modified | TOTAL: 22 pass 2 (xy-): 0 found - 9 modified | TOTAL: 22 pass 1 (yz+): 11 found - 11 modified | TOTAL: 33 pass 2 (yz+): 0 found - 11 modified | TOTAL: 33 pass 1 (yz-): 7 found - 7 modified | TOTAL: 40 pass 2 (yz-): 0 found - 7 modified | TOTAL: 40 pass 1 (xz+): 18 found - 18 modified | TOTAL: 58 pass 2 (xz+): 0 found - 18 modified | TOTAL: 58 pass 1 (xz-): 20 found - 20 modified | TOTAL: 78 pass 2 (xz-): 0 found - 20 modified | TOTAL: 78 Iteration Number : 1 pass 1 (+++): 54 found - 54 modified | TOTAL: 54 pass 2 (+++): 0 found - 54 modified | TOTAL: 54 pass 1 (+++): 56 found - 56 modified | TOTAL: 110 pass 2 (+++): 0 found - 56 modified | TOTAL: 110 pass 1 (+++): 71 found - 71 modified | TOTAL: 181 pass 2 (+++): 0 found - 71 modified | TOTAL: 181 pass 1 (+++): 59 found - 59 modified | TOTAL: 240 pass 2 (+++): 0 found - 59 modified | TOTAL: 240 Iteration Number : 1 pass 1 (++): 268 found - 268 modified | TOTAL: 268 pass 2 (++): 0 found - 268 modified | TOTAL: 268 pass 1 (+-): 337 found - 337 modified | TOTAL: 605 pass 2 (+-): 1 found - 338 modified | TOTAL: 606 pass 3 (+-): 0 found - 338 modified | TOTAL: 606 pass 1 (--): 262 found - 262 modified | TOTAL: 868 pass 2 (--): 1 found - 263 modified | TOTAL: 869 pass 3 (--): 0 found - 263 modified | TOTAL: 869 pass 1 (-+): 323 found - 323 modified | TOTAL: 1192 pass 2 (-+): 0 found - 323 modified | TOTAL: 1192 Iteration Number : 2 pass 1 (xy+): 30 found - 30 modified | TOTAL: 30 pass 2 (xy+): 0 found - 30 modified | TOTAL: 30 pass 1 (xy-): 29 found - 29 modified | TOTAL: 59 pass 2 (xy-): 0 found - 29 modified | TOTAL: 59 pass 1 (yz+): 30 found - 30 modified | TOTAL: 89 pass 2 (yz+): 0 found - 30 modified | TOTAL: 89 pass 1 (yz-): 24 found - 24 modified | TOTAL: 113 pass 2 (yz-): 0 found - 24 modified | TOTAL: 113 pass 1 (xz+): 24 found - 24 modified | TOTAL: 137 pass 2 (xz+): 0 found - 24 modified | TOTAL: 137 pass 1 (xz-): 20 found - 20 modified | TOTAL: 157 pass 2 (xz-): 0 found - 20 modified | TOTAL: 157 Iteration Number : 2 pass 1 (+++): 5 found - 5 modified | TOTAL: 5 pass 2 (+++): 0 found - 5 modified | TOTAL: 5 pass 1 (+++): 6 found - 6 modified | TOTAL: 11 pass 2 (+++): 0 found - 6 modified | TOTAL: 11 pass 1 (+++): 6 found - 6 modified | TOTAL: 17 pass 2 (+++): 0 found - 6 modified | TOTAL: 17 pass 1 (+++): 7 found - 7 modified | TOTAL: 24 pass 2 (+++): 0 found - 7 modified | TOTAL: 24 Iteration Number : 2 pass 1 (++): 17 found - 17 modified | TOTAL: 17 pass 2 (++): 0 found - 17 modified | TOTAL: 17 pass 1 (+-): 16 found - 16 modified | TOTAL: 33 pass 2 (+-): 0 found - 16 modified | TOTAL: 33 pass 1 (--): 17 found - 17 modified | TOTAL: 50 pass 2 (--): 0 found - 17 modified | TOTAL: 50 pass 1 (-+): 6 found - 6 modified | TOTAL: 56 pass 2 (-+): 0 found - 6 modified | TOTAL: 56 Iteration Number : 3 pass 1 (xy+): 1 found - 1 modified | TOTAL: 1 pass 2 (xy+): 0 found - 1 modified | TOTAL: 1 pass 1 (xy-): 5 found - 5 modified | TOTAL: 6 pass 2 (xy-): 0 found - 5 modified | TOTAL: 6 pass 1 (yz+): 4 found - 4 modified | TOTAL: 10 pass 2 (yz+): 0 found - 4 modified | TOTAL: 10 pass 1 (yz-): 4 found - 4 modified | TOTAL: 14 pass 2 (yz-): 0 found - 4 modified | TOTAL: 14 pass 1 (xz+): 3 found - 3 modified | TOTAL: 17 pass 2 (xz+): 0 found - 3 modified | TOTAL: 17 pass 1 (xz-): 4 found - 4 modified | TOTAL: 21 pass 2 (xz-): 0 found - 4 modified | TOTAL: 21 Iteration Number : 3 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 (+++): 4 found - 4 modified | TOTAL: 6 pass 2 (+++): 0 found - 4 modified | TOTAL: 6 pass 1 (+++): 0 found - 0 modified | TOTAL: 6 Iteration Number : 3 pass 1 (++): 1 found - 1 modified | TOTAL: 1 pass 2 (++): 0 found - 1 modified | TOTAL: 1 pass 1 (+-): 1 found - 1 modified | TOTAL: 2 pass 2 (+-): 0 found - 1 modified | TOTAL: 2 pass 1 (--): 2 found - 2 modified | TOTAL: 4 pass 2 (--): 0 found - 2 modified | TOTAL: 4 pass 1 (-+): 2 found - 2 modified | TOTAL: 6 pass 2 (-+): 0 found - 2 modified | TOTAL: 6 Iteration Number : 4 pass 1 (xy+): 0 found - 0 modified | TOTAL: 0 pass 1 (xy-): 0 found - 0 modified | TOTAL: 0 pass 1 (yz+): 1 found - 1 modified | TOTAL: 1 pass 2 (yz+): 0 found - 1 modified | TOTAL: 1 pass 1 (yz-): 1 found - 1 modified | TOTAL: 2 pass 2 (yz-): 0 found - 1 modified | TOTAL: 2 pass 1 (xz+): 1 found - 1 modified | TOTAL: 3 pass 2 (xz+): 0 found - 1 modified | TOTAL: 3 pass 1 (xz-): 0 found - 0 modified | TOTAL: 3 Iteration Number : 4 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 : 4 pass 1 (++): 0 found - 0 modified | TOTAL: 0 pass 1 (+-): 1 found - 1 modified | TOTAL: 1 pass 2 (+-): 0 found - 1 modified | TOTAL: 1 pass 1 (--): 1 found - 1 modified | TOTAL: 2 pass 2 (--): 0 found - 1 modified | TOTAL: 2 pass 1 (-+): 0 found - 0 modified | TOTAL: 2 Iteration Number : 5 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 : 5 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 : 5 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 = 1785 (out of 499382: 0.357442) binarizing input wm segmentation... Ambiguous edge configurations... mri_pretess done #-------------------------------------------- #@# Fill Sat Feb 17 15:09:34 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri mri_fill -a ../scripts/ponscc.cut.log -xform transforms/talairach.lta wm.mgz filled.mgz logging cutting plane coordinates to ../scripts/ponscc.cut.log... INFO: Using transforms/talairach.lta and its offset for Talairach volume ... reading input volume...done. searching for cutting planes...voxel to talairach voxel transform 0.942 -0.009 0.008 5.011; 0.008 1.170 -0.025 -45.852; -0.008 0.028 1.003 -22.045; 0.000 0.000 0.000 1.000; Looking for area (min, max) = (350, 1400) area[0] = 737 (min = 350, max = 1400), aspect = 0.41 (min = 0.10, max = 0.75) no need to search slice=5, slice_area=2558.0, min_area0 = 65536, max_area = 1400 slice=6, slice_area=1773.0, min_area0 = 2558, max_area = 1400 slice=7, slice_area=1442.0, min_area0 = 1773, max_area = 1400 slice=8, slice_area=1305.0, min_area0 = 1442, max_area = 1400 slice=9, slice_area=1418.0, min_area0 = 1305, max_area = 1400 slice=10, slice_area=1611.0, min_area0 = 1305, max_area = 1400 slice=11, slice_area=2047.0, min_area0 = 1305, max_area = 1400 slice=12, slice_area=2922.0, min_area0 = 1305, max_area = 1400 slice=13, slice_area=3968.0, min_area0 = 1305, max_area = 1400 min_slice = 8, min_area = 1305 talairach voxel to voxel transform 1.061 0.009 -0.009 -5.110; -0.007 0.854 0.021 39.676; 0.008 -0.024 0.996 20.822; 0.000 0.000 0.000 1.000; masking possible pons locations using cc cutting plane voxel to talairach voxel transform 0.942 -0.009 0.008 5.011; 0.008 1.170 -0.025 -45.852; -0.008 0.028 1.003 -22.045; 0.000 0.000 0.000 1.000; talairach cc position changed to (3.00, -6.00, 24.00) brainstem (min, max) thickness = (15,35) brainstem min height = 25 min_delta_thickness = 6 min_cont_brainstem_thickness = 8 min_cont_brainstem_height = 3 Looking for area (min, max) = (350, 790) area[0] = 2757 (min = 350, max = 790), aspect = 0.47 (min = 0.60, max = 1.20) need search nearby using +/- offset search region where offset is 3..... using +/- offset search region where offset is 6..... using +/- offset search region where offset is 9..... area[0] = 654 (min = 350, max = 790), aspect = 1.00 (min = 0.60, max = 1.20) area[1]=1, min_area0 = 10000, max_area = 790 area[2]=1, min_area0 = 10000, max_area = 790 area[3]=1, min_area0 = 10000, max_area = 790 area[4]=1, min_area0 = 10000, max_area = 790 area[5]=1, min_area0 = 10000, max_area = 790 area[6]=1, min_area0 = 10000, max_area = 790 area[7]=654, min_area0 = 10000, max_area = 790 area[8]=822, min_area0 = 654, max_area = 790 area[9]=3557, min_area0 = 654, max_area = 790 area[10]=2235, min_area0 = 654, max_area = 790 area[11]=2433, min_area0 = 654, max_area = 790 area[12]=2508, min_area0 = 654, max_area = 790 area[13]=2563, min_area0 = 654, max_area = 790 min_slice = 7, min_area = 654 talairach voxel to voxel transform 1.061 0.009 -0.009 -5.110; -0.007 0.854 0.021 39.676; 0.008 -0.024 0.996 20.822; 0.000 0.000 0.000 1.000; done. filling left hemisphere... filling volume: pass 1 of 3...total of 243809 voxels filled... filling volume: pass 2 of 3...total of 16465815 voxels filled... filling volume: pass 3 of 3...total of 244844 voxels filled...done. filling right hemisphere... filling volume: pass 1 of 3...total of 245146 voxels filled... filling volume: pass 2 of 3...total of 16464349 voxels filled... filling volume: pass 3 of 3...total of 246310 voxels filled...done. filling degenerate left hemisphere surface locations... 389 voxels filled 8 voxels filled 0 voxels filled filling degenerate right hemisphere surface locations... 402 voxels filled 13 voxels filled 0 voxels filled refilling left hemisphere... filling volume: pass 1 of 3...total of 0 voxels filled... filling volume: pass 2 of 3...total of 16465415 voxels filled... filling volume: pass 3 of 3...total of 245244 voxels filled...done. refilling right hemisphere... filling volume: pass 1 of 3...total of 0 voxels filled... filling volume: pass 2 of 3...total of 16463926 voxels filled... filling volume: pass 3 of 3...total of 246733 voxels filled...done. combining hemispheres... writing output to filled.mgz... filling took 0.5 minutes seed_search_size = 9, min_neighbors = 5 search rh wm seed point around talairach space:(21.00, -6.00, 24.00) SRC: (108.29, 130.40, 140.76) search lh wm seed point around talairach space (-15.00, -6.00, 24.00), SRC: (146.49, 130.16, 141.06) #-------------------------------------------- #@# Tessellate lh Sat Feb 17 15:10:05 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/scripts mri_pretess ../mri/filled.mgz 255 ../mri/brain.mgz ../mri/filled-pretess255.mgz Iteration Number : 1 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-): 1 found - 1 modified | TOTAL: 1 pass 2 (yz-): 0 found - 1 modified | TOTAL: 1 pass 1 (xz+): 1 found - 1 modified | TOTAL: 2 pass 2 (xz+): 0 found - 1 modified | TOTAL: 2 pass 1 (xz-): 1 found - 1 modified | TOTAL: 3 pass 2 (xz-): 0 found - 1 modified | TOTAL: 3 Iteration Number : 1 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 : 1 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 : 2 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 : 2 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 : 2 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 = 3 (out of 245248: 0.001223) Ambiguous edge configurations... mri_pretess done mri_tessellate ../mri/filled-pretess255.mgz 255 ../surf/lh.orig.nofix $Id: mri_tessellate.c,v 1.36 2011/03/02 00:04:25 nicks Exp $ $Id: mrisurf.c,v 1.693.2.7 2013/05/12 22:28:01 nicks Exp $ slice 50: 1368 vertices, 1467 faces slice 60: 5789 vertices, 6006 faces slice 70: 13079 vertices, 13367 faces slice 80: 22681 vertices, 23025 faces slice 90: 33328 vertices, 33701 faces slice 100: 45339 vertices, 45698 faces slice 110: 57407 vertices, 57838 faces slice 120: 72267 vertices, 72762 faces slice 130: 86607 vertices, 87172 faces slice 140: 101287 vertices, 101901 faces slice 150: 115386 vertices, 115993 faces slice 160: 127350 vertices, 127905 faces slice 170: 136833 vertices, 137345 faces slice 180: 144960 vertices, 145436 faces slice 190: 152155 vertices, 152586 faces slice 200: 158211 vertices, 158612 faces slice 210: 161619 vertices, 161866 faces slice 220: 161730 vertices, 161940 faces slice 230: 161730 vertices, 161940 faces slice 240: 161730 vertices, 161940 faces slice 250: 161730 vertices, 161940 faces using the conformed surface RAS to save vertex points... writing ../surf/lh.orig.nofix using vox2ras matrix: -1.000 0.000 0.000 128.000; 0.000 0.000 1.000 -128.000; 0.000 -1.000 0.000 128.000; 0.000 0.000 0.000 1.000; rm -f ../mri/filled-pretess255.mgz mris_extract_main_component ../surf/lh.orig.nofix ../surf/lh.orig.nofix counting number of connected components... 161730 voxel in cpt #1: X=-210 [v=161730,e=485820,f=323880] located at (-27.879595, -2.763019, -9.061874) For the whole surface: X=-210 [v=161730,e=485820,f=323880] One single component has been found nothing to do done #-------------------------------------------- #@# Smooth1 lh Sat Feb 17 15:10:25 PST 2018 mris_smooth -nw -seed 1234 ../surf/lh.orig.nofix ../surf/lh.smoothwm.nofix /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/scripts setting seed for random number generator to 1234 smoothing surface tessellation for 10 iterations... smoothing complete - recomputing first and second fundamental forms... #-------------------------------------------- #@# Inflation1 lh Sat Feb 17 15:10:36 PST 2018 mris_inflate -no-save-sulc ../surf/lh.smoothwm.nofix ../surf/lh.inflated.nofix /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/scripts avg radius = 45.3 mm, total surface area = 82978 mm^2 writing inflated surface to ../surf/lh.inflated.nofix inflation took 2.8 minutes Not saving sulc step 000: RMS=0.111 (target=0.015) step 005: RMS=0.085 (target=0.015) step 010: RMS=0.069 (target=0.015) step 015: RMS=0.061 (target=0.015) step 020: RMS=0.056 (target=0.015) step 025: RMS=0.052 (target=0.015) step 030: RMS=0.050 (target=0.015) step 035: RMS=0.048 (target=0.015) step 040: RMS=0.047 (target=0.015) step 045: RMS=0.046 (target=0.015) step 050: RMS=0.045 (target=0.015) step 055: RMS=0.046 (target=0.015) step 060: RMS=0.046 (target=0.015) inflation complete. Not saving sulc #-------------------------------------------- #@# QSphere lh Sat Feb 17 15:13:22 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/scripts mris_sphere -q -seed 1234 ../surf/lh.inflated.nofix ../surf/lh.qsphere.nofix doing quick spherical unfolding. setting seed for random number genererator to 1234 $Id: mris_sphere.c,v 1.57 2011/03/02 00:04:34 nicks Exp $ $Id: mrisurf.c,v 1.693.2.7 2013/05/12 22:28:01 nicks Exp $ reading original vertex positions... unfolding cortex into spherical form... scaling brain by 0.287... inflating to sphere (rms error < 2.00) 000: dt: 0.0000, rms radial error=178.060, avgs=0 005/300: dt: 0.9000, rms radial error=177.800, avgs=0 010/300: dt: 0.9000, rms radial error=177.241, avgs=0 015/300: dt: 0.9000, rms radial error=176.507, avgs=0 020/300: dt: 0.9000, rms radial error=175.676, avgs=0 025/300: dt: 0.9000, rms radial error=174.786, avgs=0 030/300: dt: 0.9000, rms radial error=173.864, avgs=0 035/300: dt: 0.9000, rms radial error=172.926, avgs=0 040/300: dt: 0.9000, rms radial error=171.980, avgs=0 045/300: dt: 0.9000, rms radial error=171.032, avgs=0 050/300: dt: 0.9000, rms radial error=170.085, avgs=0 055/300: dt: 0.9000, rms radial error=169.141, avgs=0 060/300: dt: 0.9000, rms radial error=168.201, avgs=0 065/300: dt: 0.9000, rms radial error=167.265, avgs=0 070/300: dt: 0.9000, rms radial error=166.334, avgs=0 075/300: dt: 0.9000, rms radial error=165.407, avgs=0 080/300: dt: 0.9000, rms radial error=164.485, avgs=0 085/300: dt: 0.9000, rms radial error=163.568, avgs=0 090/300: dt: 0.9000, rms radial error=162.656, avgs=0 095/300: dt: 0.9000, rms radial error=161.749, avgs=0 100/300: dt: 0.9000, rms radial error=160.846, avgs=0 105/300: dt: 0.9000, rms radial error=159.949, avgs=0 110/300: dt: 0.9000, rms radial error=159.055, avgs=0 115/300: dt: 0.9000, rms radial error=158.167, avgs=0 120/300: dt: 0.9000, rms radial error=157.283, avgs=0 125/300: dt: 0.9000, rms radial error=156.404, avgs=0 130/300: dt: 0.9000, rms radial error=155.530, avgs=0 135/300: dt: 0.9000, rms radial error=154.660, avgs=0 140/300: dt: 0.9000, rms radial error=153.795, avgs=0 145/300: dt: 0.9000, rms radial error=152.934, avgs=0 150/300: dt: 0.9000, rms radial error=152.078, avgs=0 155/300: dt: 0.9000, rms radial error=151.227, avgs=0 160/300: dt: 0.9000, rms radial error=150.380, avgs=0 165/300: dt: 0.9000, rms radial error=149.538, avgs=0 170/300: dt: 0.9000, rms radial error=148.701, avgs=0 175/300: dt: 0.9000, rms radial error=147.868, avgs=0 180/300: dt: 0.9000, rms radial error=147.039, avgs=0 185/300: dt: 0.9000, rms radial error=146.216, avgs=0 190/300: dt: 0.9000, rms radial error=145.396, avgs=0 195/300: dt: 0.9000, rms radial error=144.581, avgs=0 200/300: dt: 0.9000, rms radial error=143.771, avgs=0 205/300: dt: 0.9000, rms radial error=142.964, avgs=0 210/300: dt: 0.9000, rms radial error=142.163, avgs=0 215/300: dt: 0.9000, rms radial error=141.365, avgs=0 220/300: dt: 0.9000, rms radial error=140.572, avgs=0 225/300: dt: 0.9000, rms radial error=139.783, avgs=0 230/300: dt: 0.9000, rms radial error=138.999, avgs=0 235/300: dt: 0.9000, rms radial error=138.218, avgs=0 240/300: dt: 0.9000, rms radial error=137.442, avgs=0 245/300: dt: 0.9000, rms radial error=136.669, avgs=0 250/300: dt: 0.9000, rms radial error=135.901, avgs=0 255/300: dt: 0.9000, rms radial error=135.137, avgs=0 260/300: dt: 0.9000, rms radial error=134.377, avgs=0 265/300: dt: 0.9000, rms radial error=133.621, avgs=0 270/300: dt: 0.9000, rms radial error=132.870, avgs=0 275/300: dt: 0.9000, rms radial error=132surface projected - minimizing metric distortion... vertex spacing 0.96 +- 0.64 (0.00-->13.28) (max @ vno 90323 --> 90324) face area 0.02 +- 0.03 (-0.31-->0.63) .122, avgs=0 280/300: dt: 0.9000, rms radial error=131.379, avgs=0 285/300: dt: 0.9000, rms radial error=130.641, avgs=0 290/300: dt: 0.9000, rms radial error=129.906, avgs=0 295/300: dt: 0.9000, rms radial error=129.175, avgs=0 300/300: dt: 0.9000, rms radial error=128.449, avgs=0 spherical inflation complete. epoch 1 (K=10.0), pass 1, starting sse = 19483.33 taking momentum steps... taking momentum steps... taking momentum steps... pass 1 complete, delta sse/iter = 0.00/10 = 0.00015 epoch 2 (K=40.0), pass 1, starting sse = 3474.46 taking momentum steps... taking momentum steps... taking momentum steps... pass 1 complete, delta sse/iter = 0.00/10 = 0.00002 epoch 3 (K=160.0), pass 1, starting sse = 424.78 taking momentum steps... taking momentum steps... taking momentum steps... pass 1 complete, delta sse/iter = 0.02/10 = 0.00203 epoch 4 (K=640.0), pass 1, starting sse = 50.20 taking momentum steps... taking momentum steps... taking momentum steps... pass 1 complete, delta sse/iter = 0.13/14 = 0.00921 final writing spherical brain to ../surf/lh.qsphere.nofix spherical transformation took 0.28 hours distance error %100000.00 #-------------------------------------------- #@# Fix Topology lh Sat Feb 17 15:30:10 PST 2018 cp ../surf/lh.orig.nofix ../surf/lh.orig cp ../surf/lh.inflated.nofix ../surf/lh.inflated /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/scripts mris_fix_topology -mgz -sphere qsphere.nofix -ga -seed 1234 hcptest8_1mm lh reading spherical homeomorphism from 'qsphere.nofix' using genetic algorithm with optimized parameters setting seed for random number genererator to 1234 ************************************************************* Topology Correction Parameters retessellation mode: genetic search number of patches/generation : 10 number of generations : 10 surface mri loglikelihood coefficient : 1.0 volume mri loglikelihood coefficient : 10.0 normal dot loglikelihood coefficient : 1.0 quadratic curvature loglikelihood coefficient : 1.0 volume resolution : 2 eliminate vertices during search : 1 initial patch selection : 1 select all defect vertices : 0 ordering dependant retessellation: 0 use precomputed edge table : 0 smooth retessellated patch : 2 match retessellated patch : 1 verbose mode : 0 ************************************************************* INFO: assuming .mgz format $Id: mris_fix_topology.c,v 1.48 2011/03/02 00:04:32 nicks Exp $ $Id: mrisurf.c,v 1.693.2.7 2013/05/12 22:28:01 nicks Exp $ before topology correction, eno=-210 (nv=161730, nf=323880, ne=485820, g=106) using quasi-homeomorphic spherical map to tessellate cortical surface... Correction of the Topology Finding true center and radius of Spherical Surface...done Surface centered at (0,0,0) with radius 100.0 in 10 iterations marking ambiguous vertices... 18660 ambiguous faces found in tessellation segmenting defects... 71 defects found, arbitrating ambiguous regions... analyzing neighboring defects... -merging segment 12 into 9 -merging segment 31 into 9 -merging segment 37 into 9 -merging segment 27 into 9 -merging segment 18 into 17 -merging segment 19 into 17 -merging segment 39 into 24 -merging segment 54 into 24 -merging segment 61 into 24 62 defects to be corrected 0 vertices coincident reading input surface /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/surf/lh.qsphere.nofix... reading brain volume from brain... reading wm segmentation from wm... Computing Initial Surface Statistics -face loglikelihood: -9.3173 (-4.6586) -vertex loglikelihood: -5.9496 (-2.9748) -normal dot loglikelihood: -3.5731 (-3.5731) -quad curv loglikelihood: -5.9384 (-2.9692) Total Loglikelihood : -24.7784 CORRECTING DEFECT 0 (vertices=47, convex hull=53) After retessellation of defect 0, euler #=-50 (150892,449491,298549) : difference with theory (-59) = -9 CORRECTING DEFECT 1 (vertices=880, convex hull=540) After retessellation of defect 1, euler #=-50 (151198,450691,299443) : difference with theory (-58) = -8 CORRECTING DEFECT 2 (vertices=19, convex hull=46) After retessellation of defect 2, euler #=-49 (151206,450731,299476) : difference with theory (-57) = -8 CORRECTING DEFECT 3 (vertices=15, convex hull=62) After retessellation of defect 3, euler #=-48 (151216,450787,299523) : difference with theory (-56) = -8 CORRECTING DEFECT 4 (vertices=33, convex hull=51) After retessellation of defect 4, euler #=-47 (151224,450835,299564) : difference with theory (-55) = -8 CORRECTING DEFECT 5 (vertices=21, convex hull=61) After retessellation of defect 5, euler #=-46 (151233,450885,299606) : difference with theory (-54) = -8 CORRECTING DEFECT 6 (vertices=47, convex hull=46) After retessellation of defect 6, euler #=-45 (151244,450934,299645) : difference with theory (-53) = -8 CORRECTING DEFECT 7 (vertices=17, convex hull=39) After retessellation of defect 7, euler #=-44 (151247,450957,299666) : difference with theory (-52) = -8 CORRECTING DEFECT 8 (vertices=42, convex hull=89) After retessellation of defect 8, euler #=-43 (151272,451070,299755) : difference with theory (-51) = -8 CORRECTING DEFECT 9 (vertices=2391, convex hull=1147) After retessellation of defect 9, euler #=-44 (152158,454439,302237) : difference with theory (-50) = -6 CORRECTING DEFECT 10 (vertices=16, convex hull=27) After retessellation of defect 10, euler #=-43 (152161,454458,302254) : difference with theory (-49) = -6 CORRECTING DEFECT 11 (vertices=32, convex hull=72) After retessellation of defect 11, euler #=-42 (152171,454516,302303) : difference with theory (-48) = -6 CORRECTING DEFECT 12 (vertices=11, convex hull=18) After retessellation of defect 12, euler #=-41 (152173,454528,302314) : difference with theory (-47) = -6 CORRECTING DEFECT 13 (vertices=27, convex hull=47) After retessellation of defect 13, euler #=-40 (152185,454583,302358) : difference with theory (-46) = -6 CORRECTING DEFECT 14 (vertices=23, convex hull=55) After retessellation of defect 14, euler #=-39 (152198,454641,302404) : difference with theory (-45) = -6 CORRECTING DEFECT 15 (vertices=10, convex hull=34) After retessellation of defect 15, euler #=-38 (152199,454656,302419) : difference with theory (-44) = -6 CORRECTING DEFECT 16 (vertices=180, convex hull=204) After retessellation of defect 16, euler #=-35 (152251,454912,302626) : difference with theory (-43) = -8 CORRECTING DEFECT 17 (vertices=28, convex hull=47) After retessellation of defect 17, euler #=-34 (152260,454956,302662) : difference with theory (-42) = -8 CORRECTING DEFECT 18 (vertices=78, convex hull=107) After retessellation of defect 18, euler #=-33 (152289,455088,302766) : difference with theory (-41) = -8 CORRECTING DEFECT 19 (vertices=60, convex hull=45) After retessellation of defect 19, euler #=-32 (152294,455116,302790) : difference with theory (-40) = -8 CORRECTING DEFECT 20 (vertices=42, convex hull=28) After retessellation of defect 20, euler #=-31 (152300,455143,302812) : difference with theory (-39) = -8 CORRECTING DEFECT 21 (vertices=4711, convex hull=1689) After retessellation of defect 21, euler #=-38 (153927,461032,307067) : difference with theory (-38) = 0 CORRECTING DEFECT 22 (vertices=39, convex hull=51) After retessellation of defect 22, euler #=-37 (153943,461100,307120) : difference with theory (-37) = 0 CORRECTING DEFECT 23 (vertices=30, convex hull=30) After retessellation of defect 23, euler #=-36 (153946,461116,307134) : difference with theory (-36) = 0 CORRECTING DEFECT 24 (vertices=72, convex hull=102) After retessellation of defect 24, euler #=-35 (153973,461240,307232) : difference with theory (-35) = 0 CORRECTING DEFECT 25 (vertices=60, convex hull=75) After retessellation of defect 25, euler #=-34 (153989,461321,307298) : difference with theory (-34) = 0 CORRECTING DEFECT 26 (vertices=6, convex hull=14) Warning - incorrect dp selected!!!!(-79.096004 >= -79.096011 ) After retessellation of defect 26, euler #=-33 (153990,461327,307304) : difference with theory (-33) = 0 CORRECTING DEFECT 27 (vertices=29, convex hull=38) After retessellation of defect 27, euler #=-32 (153993,461347,307322) : difference with theory (-32) = 0 CORRECTING DEFECT 28 (vertices=34, convex hull=56) After retessellation of defect 28, euler #=-31 (154003,461398,307364) : difference with theory (-31) = 0 CORRECTING DEFECT 29 (vertices=20, convex hull=50) After retessellation of defect 29, euler #=-30 (154012,461441,307399) : difference with theory (-30) = 0 CORRECTING DEFECT 30 (vertices=10, convex hull=12) After retessellation of defect 30, euler #=-29 (154013,461446,307404) : difference with theory (-29) = 0 CORRECTING DEFECT 31 (vertices=124, convex hull=60) After retessellation of defect 31, euler #=-28 (154035,461537,307474) : difference with theory (-28) = 0 CORRECTING DEFECT 32 (vertices=497, convex hull=191) After retessellation of defect 32, euler #=-27 (154068,461723,307628) : difference with theory (-27) = 0 CORRECTING DEFECT 33 (vertices=13, convex hull=25) After retessellation of defect 33, euler #=-26 (154072,461744,307646) : difference with theory (-26) = 0 CORRECTING DEFECT 34 (vertices=9, convex hull=20) After retessellation of defect 34, euler #=-25 (154073,461754,307656) : difference with theory (-25) = 0 CORRECTING DEFECT 35 (vertices=15, convex hull=26) After retessellation of defect 35, euler #=-24 (154076,461769,307669) : difference with theory (-24) = 0 CORRECTING DEFECT 36 (vertices=68, convex hull=54) After retessellation of defect 36, euler #=-23 (154083,461812,307706) : difference with theory (-23) = 0 CORRECTING DEFECT 37 (vertices=11, convex hull=20) After retessellation of defect 37, euler #=-22 (154085,461823,307716) : difference with theory (-22) = 0 CORRECTING DEFECT 38 (vertices=31, convex hull=31) After retessellation of defect 38, euler #=-21 (154091,461856,307744) : difference with theory (-21) = 0 CORRECTING DEFECT 39 (vertices=6, convex hull=27) After retessellation of defect 39, euler #=-20 (154094,461873,307759) : difference with theory (-20) = 0 CORRECTING DEFECT 40 (vertices=33, convex hull=38) After retessellation of defect 40, euler #=-19 (154102,461912,307791) : difference with theory (-19) = 0 CORRECTING DEFECT 41 (vertices=23, convex hull=25) After retessellation of defect 41, euler #=-18 (154107,461935,307810) : difference with theory (-18) = 0 CORRECTING DEFECT 42 (vertices=6, convex hull=16) After retessellation of defect 42, euler #=-17 (154108,461941,307816) : difference with theory (-17) = 0 CORRECTING DEFECT 43 (vertices=91, convex hull=114) After retessellation of defect 43, euler #=-16 (154154,462131,307961) : difference with theory (-16) = 0 CORRECTING DEFECT 44 (vertices=21, convex hull=20) Warning - incorrect dp selected!!!!(-64.839738 >= -64.839742 ) After retessellation of defect 44, euler #=-15 (154158,462147,307974) : difference with theory (-15) = 0 CORRECTING DEFECT 45 (vertices=25, convex hull=24) After retessellation of defect 45, euler #=-14 (154162,462167,307991) : difference with theory (-14) = 0 CORRECTING DEFECT 46 (vertices=75, convex hull=104) After retessellation of defect 46, euler #=-13 (154194,462307,308100) : difference with theory (-13) = 0 CORRECTING DEFECT 47 (vertices=63, convex hull=54) After retessellation of defect 47, euler #=-12 (154203,462352,308137) : difference with theory (-12) = 0 CORRECTING DEFECT 48 (vertices=19, convex hull=19) After retessellation of defect 48, euler #=-11 (154207,462369,308151) : difference with theory (-11) = 0 CORRECTING DEFECT 49 (vertices=11, convex hull=11) After retessellation of defect 49, euler #=-10 (154207,462370,308153) : difference with theory (-10) = 0 CORRECTING DEFECT 50 (vertices=186, convex hull=109) After retessellation of defect 50, euler #=-9 (154225,462471,308237) : difference with theory (-9) = 0 CORRECTING DEFECT 51 (vertices=64, convex hull=66) After retessellation of defect 51, euler #=-8 (154240,462542,308294) : difference with theory (-8) = 0 CORRECTING DEFECT 52 (vertices=16, convex hull=33) After retessellation of defect 52, euler #=-7 (154247,462573,308319) : difference with theory (-7) = 0 CORRECTING DEFECT 53 (vertices=23, convex hull=53) After retessellation of defect 53, euler #=-6 (154254,462611,308351) : difference with theory (-6) = 0 CORRECTING DEFECT 54 (vertices=71, convex hull=69) After retessellation of defect 54, euler #=-5 (154269,462682,308408) : difference with theory (-5) = 0 CORRECTING DEFECT 55 (vertices=18, convex hull=57) After retessellation of defect 55, euler #=-4 (154278,462728,308446) : difference with theory (-4) = 0 CORRECTING DEFECT 56 (vertices=40, convex hull=50) After retessellation of defect 56, euler #=-3 (154287,462773,308483) : difference with theory (-3) = 0 CORRECTING DEFECT 57 (vertices=54, convex hull=49) After retessellation of defect 57, euler #=-2 (154300,462832,308530) : difference with theory (-2) = 0 CORRECTING DEFECT 58 (vertices=5, convex hull=16) After retessellation of defect 58, euler #=-1 (154301,462838,308536) : difference with theory (-1) = 0 CORRECTING DEFECT 59 (vertices=45, convex hull=54) After retessellation of defect 59, euler #=0 (154310,462884,308574) : difference with theory (0) = 0 CORRECTING DEFECT 60 (vertices=83, convex hull=69) After retessellation of defect 60, euler #=1 (154325,462958,308634) : difference with theory (1) = 0 CORRECTING DEFECT 61 (vertices=53, convex hull=30) After retessellation of defect 61, euler #=2 (154331,462987,308658) : difference with theory (2) = 0 computing original vertex metric properties... storing new metric properties... computing tessellation statistics... vertex spacing 0.88 +- 0.27 (0.05-->10.89) (max @ vno 113438 --> 158677) face area 0.00 +- 0.00 (0.00-->0.00) performing soap bubble on retessellated vertices for 0 iterations... vertex spacing 0.88 +- 0.27 (0.05-->10.89) (max @ vno 113438 --> 158677) face area 0.00 +- 0.00 (0.00-->0.00) tessellation finished, orienting corrected surface... 239 mutations (37.9%), 392 crossovers (62.1%), 208 vertices were eliminated building final representation... 7399 vertices and 0 faces have been removed from triangulation after topology correction, eno=2 (nv=154331, nf=308658, ne=462987, g=0) writing corrected surface to /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/surf/lh.orig... 0.000 % of the vertices (0 vertices) exhibit an orientation change topology fixing took 115.0 minutes 0 defective edges removing intersecting faces 000: 950 intersecting 001: 64 intersecting 002: 23 intersecting 003: 19 intersecting 004: 16 intersecting 005: 11 intersecting 006: 10 intersecting 007: 3 intersecting 008: 2 intersecting expanding nbhd size to 2 009: 7 intersecting mris_euler_number ../surf/lh.orig euler # = v-e+f = 2g-2: 154331 - 462987 + 308658 = 2 --> 0 holes F =2V-4: 308658 = 308662-4 (0) 2E=3F: 925974 = 925974 (0) total defect index = 0 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/scripts mris_remove_intersection ../surf/lh.orig ../surf/lh.orig intersection removal took 0.01 hours removing intersecting faces 000: 407 intersecting 001: 43 intersecting 002: 15 intersecting 003: 14 intersecting expanding nbhd size to 2 004: 15 intersecting 005: 11 intersecting 006: 10 intersecting 007: 9 intersecting 008: 6 intersecting 009: 5 intersecting 010: 3 intersecting expanding nbhd size to 3 011: 3 intersecting writing corrected surface to ../surf/lh.orig rm ../surf/lh.inflated #-------------------------------------------- #@# Make White Surf lh Sat Feb 17 17:25:43 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/scripts mris_make_surfaces -noaseg -noaparc -whiteonly -mgz -T1 brain.finalsurfs hcptest8_1mm lh only generating white matter surface not using aseg volume to prevent surfaces crossing the midline not using aparc to prevent surfaces crossing the midline INFO: assuming MGZ format for volumes. using brain.finalsurfs as T1 volume... $Id: mris_make_surfaces.c,v 1.127.2.6 2013/05/12 22:28:01 nicks Exp $ $Id: mrisurf.c,v 1.693.2.7 2013/05/12 22:28:01 nicks Exp $ reading volume /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/filled.mgz... reading volume /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/brain.finalsurfs.mgz... reading volume /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/wm.mgz... 36905 bright wm thresholded. 222 bright non-wm voxels segmented. reading original surface position from /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/surf/lh.orig... computing class statistics... border white: 316540 voxels (1.89%) border gray 328699 voxels (1.96%) WM (100.0): 100.8 +- 6.2 [70.0 --> 110.0] GM (90.0) : 88.1 +- 10.2 [30.0 --> 110.0] setting MIN_GRAY_AT_WHITE_BORDER to 71.8 (was 70) setting MAX_BORDER_WHITE to 113.2 (was 105) setting MIN_BORDER_WHITE to 82.0 (was 85) setting MAX_CSF to 61.6 (was 40) setting MAX_GRAY to 100.8 (was 95) setting MAX_GRAY_AT_CSF_BORDER to 76.9 (was 75) setting MIN_GRAY_AT_CSF_BORDER to 51.4 (was 40) repositioning cortical surface to gray/white boundary smoothing T1 volume with sigma = 2.000 vertex spacing 0.81 +- 0.24 (0.02-->8.02) (max @ vno 150989 --> 151077) face area 0.27 +- 0.14 (0.00-->9.79) mean absolute distance = 0.83 +- 1.06 4111 vertices more than 2 sigmas from mean. averaging target values for 5 iterations... smoothing contralateral hemisphere... using class modes intead of means, discounting robust sigmas.... intensity peaks found at WM=107, GM=82 mean inside = 101.0, mean outside = 85.8 smoothing surface for 5 iterations... mean border=89.2, 325 (325) missing vertices, mean dist 0.3 [0.9 (%32.1)->0.8 (%67.9))] %63 local maxima, %36 large gradients and % 0 min vals, 0 gradients ignored tol=1.0e-04, sigma=2.0, host=induc, nav=4, nbrs=2, l_repulse=5.000, l_tspring=1.000, l_nspring=0.500, l_intensity=0.200, l_curv=1.000 mom=0.00, dt=0.50 complete_dist_mat 0 rms 0 smooth_averages 0 remove_neg 0 ico_order 0 which_surface 0 target_radius 0.000000 nfields 0 scale 0.000000 desired_rms_height 0.000000 momentum 0.000000 nbhd_size 0 max_nbrs 0 niterations 25 nsurfaces 0 SURFACES 3 flags 0 (0) use curv 0 no sulc 0 no rigid align 0 mris->nsize 2 mris->hemisphere 0 randomSeed 0 smoothing T1 volume with sigma = 1.000 vertex spacing 0.90 +- 0.28 (0.06-->7.91) (max @ vno 150989 --> 151077) face area 0.27 +- 0.14 (0.00-->7.44) 000: dt: 0.0000, sse=5590735.0, rms=9.16 001: dt: 0.5000, sse=6940317.0, rms=6.645 (0.000%) 002: dt: 0.5000, sse=7375615.5, rms=5.159 (0.000%) 003: dt: 0.5000, sse=7750075.5, rms=4.281 (0.000%) 004: dt: 0.5000, sse=7979817.5, rms=3.781 (0.000%) 005: dt: 0.5000, sse=8124721.5, rms=3.494 (0.000%) 006: dt: 0.5000, sse=8181731.5, rms=3.317 (0.000%) 007: dt: 0.5000, sse=8207758.0, rms=3.212 (0.000%) 008: dt: 0.5000, sse=8243728.0, rms=3.136 (0.000%) rms = 3.09, time step reduction 1 of 3 to 0.250... 009: dt: 0.5000, sse=8216154.0, rms=3.086 (0.000%) 010: dt: 0.2500, sse=5471212.0, rms=2.476 (0.000%) 011: dt: 0.2500, sse=5200440.5, rms=2.322 (0.000%) rms = 2.28, time step reduction 2 of 3 to 0.125... 012: dt: 0.2500, sse=5042680.5, rms=2.284 (0.000%) rms = 2.25, time step reduction 3 of 3 to 0.062... 013: dt: 0.1250, sse=4955355.0, rms=2.247 (0.000%) positioning took 3.4 minutes mean border=92.3, 343 (119) missing vertices, mean dist -0.3 [0.5 (%76.5)->0.3 (%23.5))] %85 local maxima, %14 large gradients and % 0 minmean absolute distance = 0.43 +- 0.63 4791 vertices more than 2 sigmas from mean. averaging target values for 5 iterations... vals, 0 gradients ignored tol=1.0e-04, sigma=1.0, host=induc, nav=2, nbrs=2, l_repulse=5.000, l_tspring=1.000, l_nspring=0.500, l_intensity=0.200, l_curv=1.000 mom=0.00, dt=0.50 smoothing T1 volume with sigma = 0.500 vertex spacing 0.88 +- 0.27 (0.03-->7.67) (max @ vno 150989 --> 151077) face area 0.34 +- 0.18 (0.00-->9.42) mean absolute distance = 0.26 +- 0.39 4498 vertices more than 2 sigmas from mean. averaging target values for 5 iterations... 000: dt: 0.0000, sse=5581529.0, rms=4.52 014: dt: 0.5000, sse=5790391.5, rms=3.082 (0.000%) 015: dt: 0.5000, sse=6641447.0, rms=2.912 (0.000%) 016: dt: 0.5000, sse=7023981.0, rms=2.810 (0.000%) rms = 2.95, time step reduction 1 of 3 to 0.250... 017: dt: 0.2500, sse=5832915.0, rms=2.278 (0.000%) 018: dt: 0.2500, sse=5504950.5, rms=2.025 (0.000%) 019: dt: 0.2500, sse=5330016.0, rms=1.965 (0.000%) rms = 1.95, time step reduction 2 of 3 to 0.125... 020: dt: 0.2500, sse=5272200.5, rms=1.948 (0.000%) rms = 1.92, time step reduction 3 of 3 to 0.062... 021: dt: 0.1250, sse=5201224.0, rms=1.923 (0.000%) positioning took 1.9 minutes mean border=94.2, 354 (81) missing vertices, mean dist -0.1 [0.3 (%73.4)->0.2 (%26.6))] %94 local maxima, % 6 large gradients and % 0 min vals, 0 gradients ignored tol=1.0e-04, sigma=0.5, host=induc, nav=1, nbrs=2, l_repulse=5.000, l_tspring=1.000, l_nspring=0.500, l_intensity=0.200, l_curv=1.000 mom=0.00, dt=0.50 smoothing T1 volume with sigma = 0.250 vertex spacing 0.88 +- 0.27 (0.02-->7.64) (max @ vno 150989 --> 151077) face area 0.33 +- 0.17 (0.00-->9.00) mean absolute distance = 0.20 +- 0.32 4268 vertices more than 2 sigmas from mean. averaging target values for 5 iterations... 000: dt: 0.0000, sse=5345325.0, rms=3.04 022: dt: 0.5000, sse=5695110.0, rms=2.503 (0.000%) rms = 2.64, time step reduction 1 of 3 to 0.250... 023: dt: 0.2500, sse=5401291.5, rms=2.066 (0.000%) 024: dt: 0.2500, sse=5405704.5, rms=1.869 (0.000%) rms = 1.83, time step reduction 2 of 3 to 0.125... 025: dt: 0.2500, sse=5351822.0, rms=1.826 (0.000%) rms = 1.80, time step reduction 3 of 3 to 0.062... 026: dt: 0.1250, sse=5280200.5, rms=1.796 (0.000%) positioning took 1.3 minutes mean border=94.7, 405 (63) missing vertices, mean dist -0.0 [0.2 (%55.6)->0.2 (%44.4))] %95 local maxima, % 4 large gradients and % 0 min vals, 0 gradients ignored tol=1.0e-04, sigma=0.2, host=induc, nav=0, nbrs=2, l_repulse=5.000, l_tspring=1.000, l_nspring=0.500, l_intensity=0.200, l_curv=1.000 mom=0.00, dt=0.50 writing white matter surface to /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/surf/lh.white... writing smoothed curvature to lh.curv 000: dt: 0.0000, sse=5287776.5, rms=1.91 027: dt: 0.5000, sse=6974006.5, rms=1.747 (0.000%) rms = 2.25, time step reduction 1 of 3 to 0.250... 028: dt: 0.2500, sse=6255039.5, rms=1.554 (0.000%) rms = 1.57, time step reduction 2 of 3 to 0.125... rms = 1.54, time step reduction 3 of 3 to 0.062... 029: dt: 0.1250, sse=6187093.0, rms=1.536 (0.000%) positioning took 1.0 minutes writing curvature file /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/surf/lh.curv writing smoothed area to lh.area writing curvature file /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/surf/lh.area vertex spacing 0.88 +- 0.26 (0.06-->7.63) (max @ vno 150989 --> 151077) face area 0.32 +- 0.17 (0.00-->8.88) refinement took 10.5 minutes #-------------------------------------------- #@# Smooth2 lh Sat Feb 17 17:36:11 PST 2018 mris_smooth -n 3 -nw -seed 1234 ../surf/lh.white ../surf/lh.smoothwm /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/scripts smoothing for 3 iterations setting seed for random number generator to 1234 smoothing surface tessellation for 3 iterations... smoothing complete - recomputing first and second fundamental forms... #-------------------------------------------- #@# Inflation2 lh Sat Feb 17 17:36:21 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/scripts mris_inflate ../surf/lh.smoothwm ../surf/lh.inflated avg radius = 45.9 mm, total surface area = 91087 mm^2 writing inflated surface to ../surf/lh.inflated writing sulcal depths to ../surf/lh.sulc step 000: RMS=0.118 (target=0.015) step 005: RMS=0.083 (target=0.015) step 010: RMS=0.063 (target=0.015) step 015: RMS=0.053 (target=0.015) step 020: RMS=0.045 (target=0.015) step 025: RMS=0.039 (target=0.015) step 030: RMS=0.033 (target=0.015) step 035: RMS=0.028 (target=0.015) step 040: RMS=0.025 (target=0.015) step 045: RMS=0.023 (target=0.015) step 050: RMS=0.020 (target=0.015) step 055: RMS=0.019 (target=0.015) step 060: RMS=0.019 (target=0.015) inflation complete. inflation took 2.3 minutes mris_curvature -thresh .999 -n -a 5 -w -distances 10 10 ../surf/lh.inflated normalizing curvature values. averaging curvature patterns 5 times. sampling 10 neighbors out to a distance of 10 mm 226 vertices thresholded to be in k1 ~ [-0.82 0.43], k2 ~ [-0.13 0.15] total integrated curvature = 0.263*4pi (3.303) --> 1 handles ICI = 1.6, FI = 10.5, variation=183.002 172 vertices thresholded to be in [-0.06 0.02] writing Gaussian curvature to ../surf/lh.inflated.K...thresholding curvature at 99.90% level curvature mean = 0.000, std = 0.002 128 vertices thresholded to be in [-0.24 0.22] done. writing mean curvature to ../surf/lh.inflated.H...curvature mean = -0.016, std = 0.023 done. #----------------------------------------- #@# Curvature Stats lh Sat Feb 17 17:41:17 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/surf mris_curvature_stats -m --writeCurvatureFiles -G -o ../stats/lh.curv.stats -F smoothwm hcptest8_1mm lh curv sulc Toggling save flag on curvature files [ ok ] Outputting results using filestem [ ../stats/lh.curv.stats ] Toggling save flag on curvature files [ ok ] Setting surface [ hcptest8_1mm/lh.smoothwm ] Reading surface... [ ok ] Setting texture [ curv ] Reading texture... [ ok ] Setting texture [ sulc ] Reading texture...Gb_filter = 0 [ ok ] Calculating Discrete Principal Curvatures... Determining geometric order for vertex faces... [####################] [ ok ] Determining KH curvatures... [####################] [ ok ] Determining k1k2 curvatures... [####################] [ ok ] deltaViolations [ 266 ] Gb_filter = 0 WARN: S lookup min: -0.381463 WARN: S explicit min: 0.000000 vertex = 901 #-------------------------------------------- #@# Sphere lh Sat Feb 17 17:41:29 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/scripts mris_sphere -seed 1234 ../surf/lh.inflated ../surf/lh.sphere setting seed for random number genererator to 1234 $Id: mris_sphere.c,v 1.57 2011/03/02 00:04:34 nicks Exp $ $Id: mrisurf.c,v 1.693.2.7 2013/05/12 22:28:01 nicks Exp $ reading original vertex positions... unfolding cortex into spherical form... surface projected - minimizing metric distortion... scaling brain by 0.268... MRISunfold() max_passes = 1 ------- tol=5.0e-01, sigma=0.0, host=induc, nav=1024, nbrs=2, l_area=1.000, l_dist=1.000 using quadratic fit line minimization complete_dist_mat 0 rms 0 smooth_averages 0 remove_neg 0 ico_order 0 which_surface 0 target_radius 0.000000 nfields 0 scale 1.000000 desired_rms_height -1.000000 momentum 0.900000 nbhd_size 7 max_nbrs 8 niterations 25 nsurfaces 0 SURFACES 3 flags 0 (0) use curv 0 no sulc 0 no rigid align 0 mris->nsize 2 mris->hemisphere 0 randomSeed 1234 -------------------- mrisRemoveNegativeArea() pass 1: epoch 1 of 3 starting distance error %21.13 pass 1: epoch 2 of 3 starting distance error %21.08 unfolding complete - removing small folds... starting distance error %20.95 removing remaining folds... final distance error %20.97 MRISunfold() return, current seed 1234 writing spherical brain to ../surf/lh.sphere spherical transformation took 2.84 hours #-------------------------------------------- #@# Surf Reg lh Sat Feb 17 20:31:49 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/scripts mris_register -curv ../surf/lh.sphere /usr/local/freesurfer/average/lh.average.curvature.filled.buckner40.tif ../surf/lh.sphere.reg using smoothwm curvature for final alignment $Id: mris_register.c,v 1.59 2011/03/02 00:04:33 nicks Exp $ $Id: mrisurf.c,v 1.693.2.7 2013/05/12 22:28:01 nicks Exp $ reading surface from ../surf/lh.sphere... reading template parameterization from /usr/local/freesurfer/average/lh.average.curvature.filled.buckner40.tif... MRISregister() ------- max_passes = 4 min_degrees = 0.500000 max_degrees = 64.000000 nangles = 8 tol=5.0e-01, sigma=0.0, host=induc, nav=1024, nbrs=1, l_extern=10000.000, l_parea=0.200, l_nlarea=1.000, l_corr=1.000, l_dist=5.000 using quadratic fit line minimization complete_dist_mat 0 rms 0 smooth_averages 0 remove_neg 0 ico_order 0 which_surface 0 target_radius 0.000000 nfields 0 scale 0.000000 desired_rms_height -1.000000 momentum 0.950000 nbhd_size -10 max_nbrs 10 niterations 25 nsurfaces 0 SURFACES 3 flags 16 (10) use curv 16 no sulc 0 no rigid align 0 mris->nsize 1 mris->hemisphere 0 randomSeed 0 tol=5.0e-01, sigma=0.0, host=induc, nav=1024, nbrs=1, l_extern=10000.000, l_parea=0.200, l_nlarea=1.000, l_corr=1.000, l_dist=5.000 using quadratic fit line minimization -------------------- 1 Reading lh.sulc curvature mean = 0.000, std = 0.623 curvature mean = 0.042, std = 0.930 curvature mean = 0.025, std = 0.854 Starting MRISrigidBodyAlignGlobal() d=64.00 min @ (0.00, -16.00, 16.00) sse = 313201.4, tmin=3.4027 d=32.00 min @ (0.00, 8.00, 0.00) sse = 291707.2, tmin=6.8451 d=16.00 min @ (0.00, -4.00, 0.00) sse = 266215.6, tmin=10.5396 d=4.00 min @ (1.00, 1.00, 0.00) sse = 263746.1, tmin=17.5418 d=2.00 min @ (0.00, 0.00, -0.50) sse = 263364.3, tmin=21.2082 d=0.50 min @ (0.00, -0.12, 0.00) sse = 263360.4, tmin=28.2678 tol=1.0e+00, sigma=0.5, host=induc, nav=1024, nbrs=1, l_extern=10000.000, l_parea=0.200, l_nlarea=1.000, l_corr=0.050, l_spring=0.500, l_dist=5.000 using quadratic fit line minimization singular matrix in quadratic form MRISrigidBodyAlignGlobal() done 28.27 min curvature mean = 0.004, std = 0.936 curvature mean = 0.009, std = 0.933 curvature mean = -0.001, std = 0.947 curvature mean = 0.004, std = 0.967 curvature mean = -0.003, std = 0.949 curvature mean = 0.001, std = 0.984 2 Reading smoothwm curvature mean = -0.028, std = 0.409 curvature mean = 0.004, std = 0.069 curvature mean = 0.055, std = 0.238 curvature mean = 0.004, std = 0.080 curvature mean = 0.026, std = 0.374 curvature mean = 0.005, std = 0.085 curvature mean = 0.015, std = 0.479 curvature mean = 0.005, std = 0.086 curvature mean = 0.006, std = 0.574 MRISregister() return, current seed 0 writing registered surface to ../surf/lh.sphere.reg... expanding nbhd size to 1 #-------------------------------------------- #@# Jacobian white lh Sat Feb 17 22:28:13 PST 2018 mris_jacobian ../surf/lh.white ../surf/lh.sphere.reg ../surf/lh.jacobian_white reading surface from ../surf/lh.white... writing curvature file ../surf/lh.jacobian_white #-------------------------------------------- #@# AvgCurv lh Sat Feb 17 22:28:18 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/scripts mrisp_paint -a 5 /usr/local/freesurfer/average/lh.average.curvature.filled.buckner40.tif#6 ../surf/lh.sphere.reg ../surf/lh.avg_curv averaging curvature patterns 5 times... reading surface from ../surf/lh.sphere.reg... reading template parameterization from /usr/local/freesurfer/average/lh.average.curvature.filled.buckner40.tif... writing curvature file to ../surf/lh.avg_curv... #----------------------------------------- #@# Cortical Parc lh Sat Feb 17 22:28:23 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/scripts mris_ca_label -seed 1234 hcptest8_1mm lh ../surf/lh.sphere.reg /usr/local/freesurfer/average/lh.curvature.buckner40.filled.desikan_killiany.2010-03-25.gcs ../label/lh.aparc.annot setting seed for random number generator to 1234 $Id: mris_ca_label.c,v 1.35 2011/03/02 00:04:27 nicks Exp $ $Id: mrisurf.c,v 1.693.2.7 2013/05/12 22:28:01 nicks Exp $ reading atlas from /usr/local/freesurfer/average/lh.curvature.buckner40.filled.desikan_killiany.2010-03-25.gcs... reading color table from GCSA file.... average std = 1.0 using min determinant for regularization = 0.011 0 singular and 384 ill-conditioned covariance matrices regularized input 0: MEAN CURVATURE, flags 0, avgs 5, name mean_curvature labeling surface... relabeling using gibbs priors... 000: 3339 changed, 154331 examined... 001: 797 changed, 14244 examined... 002: 185 changed, 4351 examined... 003: 67 changed, 1136 examined... 004: 18 changed, 389 examined... 005: 7 changed, 117 examined... 006: 3 changed, 40 examined... 007: 3 changed, 21 examined... 008: 2 changed, 16 examined... 009: 2 changed, 17 examined... 010: 1 changed, 12 examined... 011: 0 changed, 9 examined... 000: 60 total segments, 24 labels (128 vertices) changed 001: 36 total segments, 0 labels (0 vertices) changed 10 filter iterations complete (10 requested, 63 changed) writing output to ../label/lh.aparc.annot... classification took 1 minutes and 19 seconds. #-------------------------------------------- #@# Make Pial Surf lh Sat Feb 17 22:29:43 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/scripts mris_make_surfaces -noaseg -white NOWRITE -mgz -T1 brain.finalsurfs hcptest8_1mm lh -white NOWRITE indicates that white, curv, area, and cortex.label files will not be written... not using aseg volume to prevent surfaces crossing the midline INFO: assuming MGZ format for volumes. using brain.finalsurfs as T1 volume... $Id: mris_make_surfaces.c,v 1.127.2.6 2013/05/12 22:28:01 nicks Exp $ $Id: mrisurf.c,v 1.693.2.7 2013/05/12 22:28:01 nicks Exp $ reading volume /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/filled.mgz... reading volume /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/brain.finalsurfs.mgz... reading volume /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/wm.mgz... 36905 bright wm thresholded. 222 bright non-wm voxels segmented. reading original surface position from /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/surf/lh.orig... computing class statistics... border white: 316540 voxels (1.89%) border gray 328699 voxels (1.96%) WM (100.0): 100.8 +- 6.2 [70.0 --> 110.0] GM (90.0) : 88.1 +- 10.2 [30.0 --> 110.0] setting MIN_GRAY_AT_WHITE_BORDER to 71.8 (was 70) setting MAX_BORDER_WHITE to 113.2 (was 105) setting MIN_BORDER_WHITE to 82.0 (was 85) setting MAX_CSF to 61.6 (was 40) setting MAX_GRAY to 100.8 (was 95) setting MAX_GRAY_AT_CSF_BORDER to 76.9 (was 75) setting MIN_GRAY_AT_CSF_BORDER to 51.4 (was 40) smoothing contralateral hemisphere... using class modes intead of means, discounting robust sigmas.... intensity peaks found at WM=107, GM=82 mean inside = 101.0, mean outside = 85.8 smoothing surface for 5 iterations... reading colortable from annotation file... colortable with 36 entries read (originally /autofs/space/terrier_001/users/nicks/freesurfer/average/colortable_desikan_killiany.txt) repositioning cortical surface to gray/white boundary smoothing T1 volume with sigma = 2.000 vertex spacing 0.81 +- 0.24 (0.02-->8.02) (max @ vno 150989 --> 151077) face area 0.27 +- 0.14 (0.00-->9.79) mean absolute distance = 0.83 +- 1.06 4111 vertices more than 2 sigmas from mean. averaging target values for 5 iterations... mean border=89.2, 325 (325) missing vertices, mean dist 0.3 [0.9 (%32.1)->0.8 (%67.9))] %63 local maxima, %36 large gradients and % 0 min vals, 0 gradients ignored tol=1.0e-04, sigma=2.0, host=induc, nav=4, nbrs=2, l_repulse=5.000, l_tspring=1.000, l_nspring=0.500, l_intensity=0.200, l_curv=1.000 mom=0.00, dt=0.50 complete_dist_mat 0 rms 0 smooth_averages 0 remove_neg 0 ico_order 0 which_surface 0 target_radius 0.000000 nfields 0 scale 0.000000 desired_rms_height 0.000000 momentum 0.000000 nbhd_size 0 max_nbrs 0 niterations 25 nsurfaces 0 SURFACES 3 flags 0 (0) use curv 0 no sulc 0 no rigid align 0 mris->nsize 2 mris->hemisphere 0 randomSeed 0 smoothing T1 volume with sigma = 1.000 vertex spacing 0.90 +- 0.28 (0.06-->7.91) (max @ vno 150989 --> 151077) face area 0.27 +- 0.14 (0.00-->7.44) 000: dt: 0.0000, sse=5590735.0, rms=9.16 001: dt: 0.5000, sse=6940317.0, rms=6.645 (0.000%) 002: dt: 0.5000, sse=7375615.5, rms=5.159 (0.000%) 003: dt: 0.5000, sse=7750075.5, rms=4.281 (0.000%) 004: dt: 0.5000, sse=7979817.5, rms=3.781 (0.000%) 005: dt: 0.5000, sse=8124721.5, rms=3.494 (0.000%) 006: dt: 0.5000, sse=8181731.5, rms=3.317 (0.000%) 007: dt: 0.5000, sse=8207758.0, rms=3.212 (0.000%) 008: dt: 0.5000, sse=8243728.0, rms=3.136 (0.000%) rms = 3.09, time step reduction 1 of 3 to 0.250... 009: dt: 0.5000, sse=8216154.0, rms=3.086 (0.000%) 010: dt: 0.2500, sse=5471212.0, rms=2.476 (0.000%) 011: dt: 0.2500, sse=5200440.5, rms=2.322 (0.000%) rms = 2.28, time step reduction 2 of 3 to 0.125... 012: dt: 0.2500, sse=5042680.5, rms=2.284 (0.000%) rms = 2.25, time step reduction 3 of 3 to 0.062... 013: dt: 0.1250, sse=4955355.0, rms=2.247 (0.000%) positioning took 3.1 minutes mean border=92.3, 343 (119) missing vertices, mean dist -0.3 [0.5 (%76.5)->0.3 (%23.5))] %85 local maxima, %14 large gradients and % 0 minmean absolute distance = 0.43 +- 0.63 4791 vertices more than 2 sigmas from mean. averaging target values for 5 iterations... vals, 0 gradients ignored tol=1.0e-04, sigma=1.0, host=induc, nav=2, nbrs=2, l_repulse=5.000, l_tspring=1.000, l_nspring=0.500, l_intensity=0.200, l_curv=1.000 mom=0.00, dt=0.50 smoothing T1 volume with sigma = 0.500 vertex spacing 0.88 +- 0.27 (0.03-->7.67) (max @ vno 150989 --> 151077) face area 0.34 +- 0.18 (0.00-->9.42) mean absolute distance = 0.26 +- 0.39 4498 vertices more than 2 sigmas from mean. averaging target values for 5 iterations... 000: dt: 0.0000, sse=5581529.0, rms=4.52 014: dt: 0.5000, sse=5790391.5, rms=3.082 (0.000%) 015: dt: 0.5000, sse=6641447.0, rms=2.912 (0.000%) 016: dt: 0.5000, sse=7023981.0, rms=2.810 (0.000%) rms = 2.95, time step reduction 1 of 3 to 0.250... 017: dt: 0.2500, sse=5832915.0, rms=2.278 (0.000%) 018: dt: 0.2500, sse=5504950.5, rms=2.025 (0.000%) 019: dt: 0.2500, sse=5330016.0, rms=1.965 (0.000%) rms = 1.95, time step reduction 2 of 3 to 0.125... 020: dt: 0.2500, sse=5272200.5, rms=1.948 (0.000%) rms = 1.92, time step reduction 3 of 3 to 0.062... 021: dt: 0.1250, sse=5201224.0, rms=1.923 (0.000%) positioning took 2.0 minutes mean border=94.2, 354 (81) missing vertices, mean dist -0.1 [0.3 (%73.4)->0.2 (%26.6))] %94 local maxima, % 6 large gradients and % 0 min vals, 0 gradients ignored tol=1.0e-04, sigma=0.5, host=induc, nav=1, nbrs=2, l_repulse=5.000, l_tspring=1.000, l_nspring=0.500, l_intensity=0.200, l_curv=1.000 mom=0.00, dt=0.50 smoothing T1 volume with sigma = 0.250 vertex spacing 0.88 +- 0.27 (0.02-->7.64) (max @ vno 150989 --> 151077) face area 0.33 +- 0.17 (0.00-->9.00) mean absolute distance = 0.20 +- 0.32 4268 vertices more than 2 sigmas from mean. averaging target values for 5 iterations... 000: dt: 0.0000, sse=5345325.0, rms=3.04 022: dt: 0.5000, sse=5695110.0, rms=2.503 (0.000%) rms = 2.64, time step reduction 1 of 3 to 0.250... 023: dt: 0.2500, sse=5401291.5, rms=2.066 (0.000%) 024: dt: 0.2500, sse=5405704.5, rms=1.869 (0.000%) rms = 1.83, time step reduction 2 of 3 to 0.125... 025: dt: 0.2500, sse=5351822.0, rms=1.826 (0.000%) rms = 1.80, time step reduction 3 of 3 to 0.062... 026: dt: 0.1250, sse=5280200.5, rms=1.796 (0.000%) positioning took 1.4 minutes mean border=94.7, 405 (63) missing vertices, mean dist -0.0 [0.2 (%55.6)->0.2 (%44.4))] %95 local maxima, % 4 large gradients and % 0 min vals, 0 gradients ignored tol=1.0e-04, sigma=0.2, host=induc, nav=0, nbrs=2, l_repulse=5.000, l_tspring=1.000, l_nspring=0.500, l_intensity=0.200, l_curv=1.000 mom=0.00, dt=0.50 repositioning cortical surface to gray/csf boundary. smoothing T1 volume with sigma = 2.000 averaging target values for 5 iterations... 000: dt: 0.0000, sse=5287776.5, rms=1.91 027: dt: 0.5000, sse=6974006.5, rms=1.747 (0.000%) rms = 2.25, time step reduction 1 of 3 to 0.250... 028: dt: 0.2500, sse=6255039.5, rms=1.554 (0.000%) rms = 1.57, time step reduction 2 of 3 to 0.125... rms = 1.54, time step reduction 3 of 3 to 0.062... 029: dt: 0.1250, sse=6187093.0, rms=1.536 (0.000%) positioning took 0.9 minutes smoothing surface for 5 iterations... mean border=72.5, 449 (449) missing vertices, mean dist 1.8 [1.3 (%0.1)->2.4 (%99.9))] %26 local maxima, %47 large gradients and %27 min vals, 1216 gradients ignored tol=1.0e-04, sigma=2.0, host=induc, nav=16, nbrs=2, l_surf_repulse=5.000, l_tspring=1.000, l_nspring=0.500, l_intensity=0.200, l_curv=1.000 mom=0.00, dt=0.50 000: dt: 0.0000, sse=19246452.0, rms=23.03 001: dt: 0.5000, sse=15143393.0, rms=19.842 (0.000%) 002: dt: 0.5000, sse=12191153.0, rms=17.166 (0.000%) 003: dt: 0.5000, sse=10279506.0, rms=15.025 (0.000%) 004: dt: 0.5000, sse=9116752.0, rms=13.399 (0.000%) 005: dt: 0.5000, sse=8514901.0, rms=12.191 (0.000%) 006: dt: 0.5000, sse=8213395.0, rms=11.267 (0.000%) 007: dt: 0.5000, sse=8058284.5, rms=10.402 (0.000%) 008: dt: 0.5000, sse=7907520.5, rms=9.499 (0.000%) 009: dt: 0.5000, sse=7718584.5, rms=8.502 (0.000%) 010: dt: 0.5000, sse=7639049.0, rms=7.470 (0.000%) 011: dt: 0.5000, sse=7563677.5, rms=6.474 (0.000%) 012: dt: 0.5000, sse=7635113.5, rms=5.621 (0.000%) 013: dt: 0.5000, sse=7804141.0, rms=5.045 (0.000%) 014: dt: 0.5000, sse=7995039.5, rms=4.704 (0.000%) 015: dt: 0.5000, sse=8092608.0, rms=4.546 (0.000%) 016: dt: 0.5000, sse=8185942.5, rms=4.438 (0.000%) rms = 4.40, time step reduction 1 of 3 to 0.250... 017: dt: 0.5000, sse=8209362.0, rms=4.398 (0.000%) 018: dt: 0.2500, sse=5857457.5, rms=3.633 (0.000%) 01smoothing T1 volume with sigma = 1.000 averaging target values for 5 iterations... 9: dt: 0.2500, sse=5698046.5, rms=3.425 (0.000%) rms = 3.40, time step reduction 2 of 3 to 0.125... 020: dt: 0.2500, sse=5534568.5, rms=3.397 (0.000%) 021: dt: 0.1250, sse=5220470.0, rms=3.192 (0.000%) rms = 3.15, time step reduction 3 of 3 to 0.062... 022: dt: 0.1250, sse=5171064.0, rms=3.151 (0.000%) positioning took 5.2 minutes mean border=69.9, 1668 (155) missing vertices, mean dist 0.2 [0.2 (%37.9)->0.5 (%62.1))] %51 local maxima, %26 large gradients and %22 min vals, 389 gradients ignored tol=1.0e-04, sigma=1.0, host=induc, nav=8, nbrs=2, l_surf_repulse=5.000, l_tspring=1.000, l_nspring=0.500, l_intensity=0.200, l_curv=1.000 mom=0.00, dt=0.50 smoothing T1 volume with sigma = 0.500 averaging target values for 5 iterations... 000: dt: 0.0000, sse=5947534.5, rms=5.16 023: dt: 0.5000, sse=6283161.0, rms=4.551 (0.000%) 024: dt: 0.5000, sse=7755336.0, rms=4.454 (0.000%) rms = 4.53, time step reduction 1 of 3 to 0.250... 025: dt: 0.2500, sse=6446685.0, rms=3.654 (0.000%) 026: dt: 0.2500, sse=5958826.5, rms=3.362 (0.000%) 027: dt: 0.2500, sse=5948685.5, rms=3.307 (0.000%) 028: dt: 0.2500, sse=5916250.0, rms=3.255 (0.000%) rms = 3.24, time step reduction 2 of 3 to 0.125... 029: dt: 0.2500, sse=5924853.0, rms=3.238 (0.000%) 030: dt: 0.1250, sse=5603864.5, rms=2.979 (0.000%) rms = 2.93, time step reduction 3 of 3 to 0.062... 031: dt: 0.1250, sse=5573007.0, rms=2.930 (0.000%) positioning took 2.3 minutes mean border=68.1, 2100 (124) missing vertices, mean dist 0.1 [0.2 (%31.9)->0.3 (%68.1))] %67 local maxima, %10 large gradients and %22 min vals, 464 gradients ignored tol=1.0e-04, sigma=0.5, host=induc, nav=4, nbrs=2, l_surf_repulse=5.000, l_tspring=1.000, l_nspring=0.500, l_intensity=0.200, l_curv=1.000 mom=0.00, dt=0.50 smoothing T1 volume with sigma = 0.250 averaging target values for 5 iterations... 000: dt: 0.0000, sse=5782096.0, rms=3.86 rms = 4.29, time step reduction 1 of 3 to 0.250... 032: dt: 0.2500, sse=5560707.0, rms=3.351 (0.000%) 033: dt: 0.2500, sse=5544660.5, rms=3.112 (0.000%) rms = 3.08, time step reduction 2 of 3 to 0.125... 034: dt: 0.2500, sse=5753238.5, rms=3.085 (0.000%) 035: dt: 0.1250, sse=5548768.0, rms=2.907 (0.000%) rms = 2.87, time step reduction 3 of 3 to 0.062... 036: dt: 0.1250, sse=5549419.0, rms=2.867 (0.000%) positioning took 1.4 minutes mean border=67.3, 3976 (113) missing vertices, mean dist 0.0 [0.2 (%42.9)->0.2 (%57.1))] %67 local maxima, %10 large gradients and %21 min vals, 334 gradients ignored tol=1.0e-04, sigma=0.2, host=induc, nav=2, nbrs=2, l_surf_repulse=5.000, l_tspring=1.000, l_nspring=0.500, l_intensity=0.200, l_curv=1.000 mom=0.00, dt=0.50 writing pial surface to /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/surf/lh.pial... writing smoothed curvature to lh.curv.pial 000: dt: 0.0000, sse=5573374.0, rms=3.04 rms = 3.70, time step reduction 1 of 3 to 0.250... 037: dt: 0.2500, sse=5503589.5, rms=2.878 (0.000%) rms = 2.84, time step reduction 2 of 3 to 0.125... 038: dt: 0.2500, sse=5755182.0, rms=2.842 (0.000%) 039: dt: 0.1250, sse=5629040.5, rms=2.767 (0.000%) rms = 2.72, time step reduction 3 of 3 to 0.062... 040: dt: 0.1250, sse=5669068.5, rms=2.724 (0.000%) positioning took 1.0 minutes writing curvature file /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/surf/lh.curv.pial writing smoothed area to lh.area.pial writing curvature file /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/surf/lh.area.pial vertex spacing 0.98 +- 0.42 (0.04-->7.04) (max @ vno 150989 --> 151077) face area 0.39 +- 0.30 (0.00-->8.26) measuring cortical thickness... 0 of 154331 vertices processed 25000 of 154331 vertices processed 50000 of 154331 vertices processed 75000 of 154331 vertices processed 100000 of 154331 vertices processed 125000 of 154331 vertices processed 150000 of 154331 vertices processed 0 of 154331 vertices processed 25000 of 154331 vertices processed 50000 of 154331 vertices processed 75000 of 154331 vertices processed 100000 of 154331 vertices processed 125000 of 154331 vertices processed 150000 of 154331 vertices processed thickness calculation complete, 696:1155 truncations. 36813 vertices at 0 distance 111790 vertices at 1 distance 101284 vertices at 2 distance 40604 vertices at 3 distance 11995 vertices at 4 distance 3653 vertices at 5 distance 1250 vertices at 6 distance 494 vertices at 7 distance 261 vertices at 8 distance 137 vertices at 9 distance 87 vertices at 10 distance 64 vertices at 11 distance 35 vertices at 12 distance 40 vertices at 13 distance 20 vertices at 14 distance 18 vertices at 15 distance 18 vertices at 16 distance 26 verticwriting cortical thickness estimate to 'thickness' file. es at 17 distance 27 vertices at 18 distance 23 vertices at 19 distance 23 vertices at 20 distance writing curvature file /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/surf/lh.thickness positioning took 23.6 minutes #-------------------------------------------- #@# Surf Volume lh Sat Feb 17 22:53:22 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/surf mris_calc -o lh.area.mid lh.area add lh.area.pial Saving result to 'lh.area.mid' (type = MRI_CURV_FILE) [ ok ] mris_calc -o lh.area.mid lh.area.mid div 2 Saving result to 'lh.area.mid' (type = MRI_CURV_FILE) [ ok ] mris_calc -o lh.volume lh.area.mid mul lh.thickness Saving result to 'lh.volume' (type = MRI_CURV_FILE) [ ok ] #----------------------------------------- #@# WM/GM Contrast lh Sat Feb 17 22:53:23 PST 2018 /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/scripts pctsurfcon --s hcptest8_1mm --lh-only Log file is /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/scripts/pctsurfcon.log Sat Feb 17 22:53:23 PST 2018 setenv SUBJECTS_DIR /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w cd /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/scripts /usr/local/freesurfer/bin/pctsurfcon $Id: pctsurfcon,v 1.11.2.1 2011/11/10 20:37:10 nicks Exp $ Linux induction.sdsc.edu 2.6.18-419.el5 #1 SMP Fri Feb 24 22:47:42 UTC 2017 x86_64 x86_64 x86_64 GNU/Linux FREESURFER_HOME /usr/local/freesurfer mri_vol2surf --mov /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/rawavg.mgz --hemi lh --noreshape --interp trilinear --projdist -1 --o /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/surf/tmp.pctsurfcon.32625/lh.wm.mgh --regheader hcptest8_1mm --cortex No such file or directory mri_vol2surf: could not open label file /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/label/lh.cortex.label srcvol = /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/rawavg.mgz srcreg unspecified srcregold = 0 srcwarp unspecified surf = white hemi = lh ProjDist = -1 reshape = 0 interp = trilinear float2int = round GetProjMax = 0 INFO: float2int code = 0 Done loading volume Computing registration from header. Using /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/mri/orig.mgz as target reference. Loading label /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/label/lh.cortex.label Invalid argument mri_vol2surf: could not load label file /data/EDresearch/Temperament_fMRI/hcptest8_1mm/proc/T1w/hcptest8_1mm/label/lh.cortex.label Invalid argument Linux induction.sdsc.edu 2.6.18-419.el5 #1 SMP Fri Feb 24 22:47:42 UTC 2017 x86_64 x86_64 x86_64 GNU/Linux recon-all -s hcptest8_1mm exited with ERRORS at Sat Feb 17 22:53:25 PST 2018 To report a problem, see http://surfer.nmr.mgh.harvard.edu/fswiki/BugReporting