Mon Sep 11 09:46:13 CEST 2017 /home/gc/study/recon-all/400614bash /usr/local/freesurfer/bin/recon-all -all -cw256 -3T -multistrip -clean-bm -i /home/MRIdata/PUD/31148_MRI_sMRI_400614.nii -s /home/gc/study/recon-all/400614bash subjid 400614bash setenv SUBJECTS_DIR /home/gc/study/recon-all FREESURFER_HOME /usr/local/freesurfer Actual FREESURFER_HOME /usr/local/freesurfer build-stamp.txt: freesurfer-Linux-centos6_x86_64-stable-pub-v6.0.0-2beb96c Linux lugh.fisica.uniud.it 2.6.32-642.4.2.el6.x86_64 #1 SMP Tue Aug 23 11:15:56 CDT 2016 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 64 kbytes maxproc 1024 total used free shared buffers cached Mem: 12188716 2875524 9313192 3172 375532 1948928 -/+ buffers/cache: 551064 11637652 Swap: 6160380 231792 5928588 ######################################## program versions used $Id: recon-all,v 1.580.2.16 2017/01/18 14:11:24 zkaufman Exp $ $Id: mri_motion_correct.fsl,v 1.15 2016/02/16 17:17:20 zkaufman Exp $ mri_convert.bin -all-info ProgramName: mri_convert.bin ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:13-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mri_convert.c,v 1.226 2016/02/26 16:15:24 mreuter Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 FLIRT version 5.5 $Id: talairach_avi,v 1.13 2015/12/23 04:25:17 greve Exp $ mri_convert.bin --version stable6 ProgramName: tkregister2_cmdl ProgramArguments: --all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:13-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: tkregister2.c,v 1.132.2.1 2016/08/02 21:17:29 greve Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 Program nu_correct, built from: Package MNI N3, version 1.12.0, compiled by nicks@terrier (x86_64-unknown-linux-gnu) on 2015-06-19 at 01:25:34 ProgramName: mri_make_uchar ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:14-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mri_make_uchar.c,v 1.4 2011/03/02 00:04:14 nicks Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mri_normalize ProgramArguments: -all-info ProgramVersion: $Name: $ TimeStamp: 2017/09/11-07:46:14-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mri_normalize.c,v 1.88.2.3 2016/12/27 16:47:13 zkaufman Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mri_watershed ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:14-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mri_watershed.cpp,v 1.103 2016/06/17 18:00:49 zkaufman Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mri_gcut ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:14-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mri_gcut.cpp,v 1.14 2011/03/02 00:04:16 nicks Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mri_segment ProgramArguments: -all-info ProgramVersion: $Name: $ TimeStamp: 2017/09/11-07:46:14-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mri_segment.c,v 1.43.2.1 2016/10/27 22:24:52 zkaufman Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mri_label2label.bin ProgramArguments: -all-info ProgramVersion: $Name: $ TimeStamp: 2017/09/11-07:46:14-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mri_label2label.c,v 1.48.2.2 2016/12/12 14:15:26 zkaufman Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mri_em_register ProgramArguments: -all-info ProgramVersion: $Name: $ TimeStamp: 2017/09/11-07:46:14-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mri_em_register.c,v 1.105.2.1 2016/10/27 22:25:10 zkaufman Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mri_ca_normalize ProgramArguments: -all-info ProgramVersion: $Name: $ TimeStamp: 2017/09/11-07:46:14-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mri_ca_normalize.c,v 1.67.2.2 2016/10/27 22:25:09 zkaufman Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mri_ca_register ProgramArguments: -all-info ProgramVersion: $Name: $ TimeStamp: 2017/09/11-07:46:14-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mri_ca_register.c,v 1.96.2.3 2016/10/27 22:25:10 zkaufman Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mri_ca_label ProgramArguments: -all-info ProgramVersion: $Name: $ TimeStamp: 2017/09/11-07:46:14-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mri_ca_label.c,v 1.113.2.2 2016/10/27 22:25:10 zkaufman Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mri_pretess ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:14-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mri_pretess.c,v 1.22 2013/08/30 18:12:25 mreuter Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mri_fill ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:14-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mri_fill.c,v 1.119 2011/10/25 14:09:58 fischl Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mri_tessellate ProgramArguments: -all-info ProgramVersion: $Name: $ TimeStamp: 2017/09/11-07:46:14-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mri_tessellate.c,v 1.38.2.1 2016/07/26 18:46:38 zkaufman Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mri_concatenate_lta.bin ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:14-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mri_concatenate_lta.c,v 1.16 2015/11/21 00:06:20 greve Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mri_normalize_tp2 ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:14-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mri_normalize_tp2.c,v 1.8 2011/03/02 00:04:23 nicks Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mris_smooth ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:14-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mris_smooth.c,v 1.30 2014/01/21 18:48:21 fischl Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mris_inflate ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:14-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mris_inflate.c,v 1.45 2016/01/20 23:42:15 greve Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mris_curvature ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:14-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mris_curvature.c,v 1.31 2011/03/02 00:04:30 nicks Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mris_sphere ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:14-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mris_sphere.c,v 1.61 2016/01/20 23:42:15 greve Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mris_fix_topology ProgramArguments: -all-info ProgramVersion: $Name: $ TimeStamp: 2017/09/11-07:46:14-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mris_fix_topology.c,v 1.50.2.1 2016/10/27 22:25:58 zkaufman Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mris_topo_fixer ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:15-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mris_topo_fixer.cpp,v 1.29 2011/03/02 00:04:34 nicks Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mris_ca_label ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:15-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mris_ca_label.c,v 1.37 2014/02/04 17:46:42 fischl Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mris_euler_number ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:15-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mris_euler_number.c,v 1.10 2013/01/14 22:39:14 greve Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mris_make_surfaces ProgramArguments: -all-info ProgramVersion: $Name: $ TimeStamp: 2017/09/11-07:46:15-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mris_make_surfaces.c,v 1.164.2.4 2016/12/13 22:26:32 zkaufman Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mris_register ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:15-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mris_register.c,v 1.63 2016/01/20 23:43:04 greve Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mris_volmask ProgramArguments: --all-info ProgramVersion: $Name: $ TimeStamp: 2017/09/11-07:46:15-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mris_volmask.cpp,v 1.26.2.2 2016/11/18 20:05:18 zkaufman Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mris_anatomical_stats ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:15-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mris_anatomical_stats.c,v 1.79 2016/03/14 15:15:34 greve Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mrisp_paint ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:15-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mrisp_paint.c,v 1.12 2016/03/22 14:47:57 fischl Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mris_curvature_stats ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:15-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mris_curvature_stats.c,v 1.65 2015/06/04 20:50:51 nicks Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mris_calc ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:15-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mris_calc.c,v 1.54.2.1 2016/09/27 18:51:28 greve Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 $Id: mri_robust_register.cpp,v 1.77 2016/01/20 23:36:17 greve Exp $ ProgramName: mri_robust_register.bin ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:15-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mri_robust_register.cpp,v 1.77 2016/01/20 23:36:17 greve Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 $Id: mri_robust_template.cpp,v 1.54 2016/05/05 21:17:08 mreuter Exp $ ProgramName: mri_robust_template ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:15-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mri_robust_template.cpp,v 1.54 2016/05/05 21:17:08 mreuter Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mri_and ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:15-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mri_and.c,v 1.4 2011/03/02 00:04:13 nicks Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mri_or ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:15-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mri_or.c,v 1.5 2013/03/20 15:03:29 lzollei Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mri_fuse_segmentations ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:15-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mri_fuse_segmentations.c,v 1.8 2011/03/02 00:04:15 nicks Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mri_segstats ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:15-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mri_segstats.c,v 1.121 2016/05/31 17:27:11 greve Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ProgramName: mri_relabel_hypointensities ProgramArguments: -all-info ProgramVersion: $Name: stable6 $ TimeStamp: 2017/09/11-07:46:15-GMT BuildTimeStamp: Jan 18 2017 16:38:58 CVS: $Id: mri_relabel_hypointensities.c,v 1.13 2015/05/15 18:44:10 nicks Exp $ User: gc Machine: lugh.fisica.uniud.it Platform: Linux PlatformVersion: 2.6.32-642.4.2.el6.x86_64 CompilerName: GCC CompilerVersion: 40400 ####################################### GCADIR /usr/local/freesurfer/average GCA RB_all_2016-05-10.vc700.gca GCASkull RB_all_withskull_2016-05-10.vc700.gca AvgCurvTif folding.atlas.acfb40.noaparc.i12.2016-08-02.tif GCSDIR /usr/local/freesurfer/average GCS DKaparc.atlas.acfb40.noaparc.i12.2016-08-02.gcs ####################################### mv -f /home/gc/study/recon-all/400614bash/mri/optimal_preflood_height /home/gc/study/recon-all/400614bash/trash mv: cannot stat `/home/gc/study/recon-all/400614bash/mri/optimal_preflood_height': No such file or directory mv -f /home/gc/study/recon-all/400614bash/mri/optimal_skullstrip_invol /home/gc/study/recon-all/400614bash/trash mv: cannot stat `/home/gc/study/recon-all/400614bash/mri/optimal_skullstrip_invol': No such file or directory mv -f /home/gc/study/recon-all/400614bash/mri/brainmask.mgz /home/gc/study/recon-all/400614bash/trash mv: cannot stat `/home/gc/study/recon-all/400614bash/mri/brainmask.mgz': No such file or directory -cw256 option is now persistent (remove with -clean-cw256) /home/gc/study/recon-all/400614bash mri_convert /home/MRIdata/PUD/31148_MRI_sMRI_400614.nii /home/gc/study/recon-all/400614bash/mri/orig/001.mgz mri_convert.bin /home/MRIdata/PUD/31148_MRI_sMRI_400614.nii /home/gc/study/recon-all/400614bash/mri/orig/001.mgz $Id: mri_convert.c,v 1.226 2016/02/26 16:15:24 mreuter Exp $ reading from /home/MRIdata/PUD/31148_MRI_sMRI_400614.nii... TR=0.00, TE=0.00, TI=0.00, flip angle=0.00 i_ras = (0.0266636, -0.998354, 0.0507764) j_ras = (-0.0789969, -0.05274, -0.995479) k_ras = (0.996518, 0.0225319, -0.0802731) writing to /home/gc/study/recon-all/400614bash/mri/orig/001.mgz... #-------------------------------------------- #@# MotionCor Mon Sep 11 09:46:20 CEST 2017 Found 1 runs /home/gc/study/recon-all/400614bash/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 /home/gc/study/recon-all/400614bash/mri/orig/001.mgz /home/gc/study/recon-all/400614bash/mri/rawavg.mgz /home/gc/study/recon-all/400614bash mri_convert /home/gc/study/recon-all/400614bash/mri/rawavg.mgz /home/gc/study/recon-all/400614bash/mri/orig.mgz --conform --cw256 mri_convert.bin /home/gc/study/recon-all/400614bash/mri/rawavg.mgz /home/gc/study/recon-all/400614bash/mri/orig.mgz --conform --cw256 $Id: mri_convert.c,v 1.226 2016/02/26 16:15:24 mreuter Exp $ reading from /home/gc/study/recon-all/400614bash/mri/rawavg.mgz... TR=0.00, TE=0.00, TI=0.00, flip angle=0.00 i_ras = (0.0266636, -0.998354, 0.0507764) j_ras = (-0.0789969, -0.05274, -0.995479) k_ras = (0.996518, 0.0225319, -0.0802731) changing data type from float to uchar (noscale = 0)... MRIchangeType: Building histogram Reslicing using trilinear interpolation writing to /home/gc/study/recon-all/400614bash/mri/orig.mgz... mri_add_xform_to_header -c /home/gc/study/recon-all/400614bash/mri/transforms/talairach.xfm /home/gc/study/recon-all/400614bash/mri/orig.mgz /home/gc/study/recon-all/400614bash/mri/orig.mgz INFO: extension is mgz #-------------------------------------------- #@# Talairach Mon Sep 11 09:46:30 CEST 2017 /home/gc/study/recon-all/400614bash/mri mri_nu_correct.mni --no-rescale --i orig.mgz --o orig_nu.mgz --n 1 --proto-iters 1000 --distance 50 /home/gc/study/recon-all/400614bash/mri /usr/local/freesurfer/bin/mri_nu_correct.mni --no-rescale --i orig.mgz --o orig_nu.mgz --n 1 --proto-iters 1000 --distance 50 nIters 1 $Id: mri_nu_correct.mni,v 1.27 2016/02/26 16:19:49 mreuter Exp $ Linux lugh.fisica.uniud.it 2.6.32-642.4.2.el6.x86_64 #1 SMP Tue Aug 23 11:15:56 CDT 2016 x86_64 x86_64 x86_64 GNU/Linux Mon Sep 11 09:46:30 CEST 2017 Program nu_correct, built from: Package MNI N3, version 1.12.0, compiled by nicks@terrier (x86_64-unknown-linux-gnu) on 2015-06-19 at 01:25:34 /usr/bin/bc tmpdir is ./tmp.mri_nu_correct.mni.8492 /home/gc/study/recon-all/400614bash/mri mri_convert orig.mgz ./tmp.mri_nu_correct.mni.8492/nu0.mnc -odt float mri_convert.bin orig.mgz ./tmp.mri_nu_correct.mni.8492/nu0.mnc -odt float $Id: mri_convert.c,v 1.226 2016/02/26 16:15:24 mreuter Exp $ reading from orig.mgz... TR=0.00, TE=0.00, TI=0.00, flip angle=0.00 i_ras = (-1, 1.86265e-09, -7.45058e-09) j_ras = (-1.49012e-08, -2.67755e-09, -1) k_ras = (-1.86265e-09, 1, -3.14321e-09) changing data type from uchar to float (noscale = 0)... writing to ./tmp.mri_nu_correct.mni.8492/nu0.mnc... -------------------------------------------------------- Iteration 1 Mon Sep 11 09:46:33 CEST 2017 nu_correct -clobber ./tmp.mri_nu_correct.mni.8492/nu0.mnc ./tmp.mri_nu_correct.mni.8492/nu1.mnc -tmpdir ./tmp.mri_nu_correct.mni.8492/0/ -iterations 1000 -distance 50 [gc@lugh.fisica.uniud.it:/home/gc/study/recon-all/400614bash/mri/] [2017-09-11 09:46:33] running: /usr/local/freesurfer/mni/bin/nu_estimate_np_and_em -parzen -log -sharpen 0.15 0.01 -iterations 1000 -stop 0.001 -shrink 4 -auto_mask -nonotify -b_spline 1.0e-7 -distance 50 -quiet -execute -clobber -nokeeptmp -tmpdir ./tmp.mri_nu_correct.mni.8492/0/ ./tmp.mri_nu_correct.mni.8492/nu0.mnc ./tmp.mri_nu_correct.mni.8492/nu1.imp Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Number of iterations: 81 CV of field change: 0.000954592 mri_convert ./tmp.mri_nu_correct.mni.8492/nu1.mnc orig_nu.mgz --like orig.mgz --conform mri_convert.bin ./tmp.mri_nu_correct.mni.8492/nu1.mnc orig_nu.mgz --like orig.mgz --conform $Id: mri_convert.c,v 1.226 2016/02/26 16:15:24 mreuter Exp $ reading from ./tmp.mri_nu_correct.mni.8492/nu1.mnc... TR=0.00, TE=0.00, TI=0.00, flip angle=0.00 i_ras = (-1, 1.86265e-09, -7.45058e-09) j_ras = (-1.49012e-08, -2.67755e-09, -1) k_ras = (-1.86265e-09, 1, -3.14321e-09) INFO: transform src into the like-volume: orig.mgz changing data type from float to uchar (noscale = 0)... MRIchangeType: Building histogram writing to orig_nu.mgz... Mon Sep 11 09:48:03 CEST 2017 mri_nu_correct.mni done talairach_avi --i orig_nu.mgz --xfm transforms/talairach.auto.xfm --atlas 3T18yoSchwartzReactN32_as_orig talairach_avi log file is transforms/talairach_avi.log... Started at Mon Sep 11 09:48:03 CEST 2017 Ended at Mon Sep 11 09:48:39 CEST 2017 talairach_avi done cp transforms/talairach.auto.xfm transforms/talairach.xfm #-------------------------------------------- #@# Talairach Failure Detection Mon Sep 11 09:48:41 CEST 2017 /home/gc/study/recon-all/400614bash/mri talairach_afd -T 0.005 -xfm transforms/talairach.xfm talairach_afd: Talairach Transform: transforms/talairach.xfm OK (p=0.7600, pval=0.6675 >= threshold=0.0050) awk -f /usr/local/freesurfer/bin/extract_talairach_avi_QA.awk /home/gc/study/recon-all/400614bash/mri/transforms/talairach_avi.log tal_QC_AZS /home/gc/study/recon-all/400614bash/mri/transforms/talairach_avi.log TalAviQA: 0.97713 z-score: 0 #-------------------------------------------- #@# Nu Intensity Correction Mon Sep 11 09:48:41 CEST 2017 mri_nu_correct.mni --i orig.mgz --o nu.mgz --uchar transforms/talairach.xfm --proto-iters 1000 --distance 50 --n 1 /home/gc/study/recon-all/400614bash/mri /usr/local/freesurfer/bin/mri_nu_correct.mni --i orig.mgz --o nu.mgz --uchar transforms/talairach.xfm --proto-iters 1000 --distance 50 --n 1 nIters 1 $Id: mri_nu_correct.mni,v 1.27 2016/02/26 16:19:49 mreuter Exp $ Linux lugh.fisica.uniud.it 2.6.32-642.4.2.el6.x86_64 #1 SMP Tue Aug 23 11:15:56 CDT 2016 x86_64 x86_64 x86_64 GNU/Linux Mon Sep 11 09:48:41 CEST 2017 Program nu_correct, built from: Package MNI N3, version 1.12.0, compiled by nicks@terrier (x86_64-unknown-linux-gnu) on 2015-06-19 at 01:25:34 /usr/bin/bc tmpdir is ./tmp.mri_nu_correct.mni.9713 /home/gc/study/recon-all/400614bash/mri mri_convert orig.mgz ./tmp.mri_nu_correct.mni.9713/nu0.mnc -odt float mri_convert.bin orig.mgz ./tmp.mri_nu_correct.mni.9713/nu0.mnc -odt float $Id: mri_convert.c,v 1.226 2016/02/26 16:15:24 mreuter Exp $ reading from orig.mgz... TR=0.00, TE=0.00, TI=0.00, flip angle=0.00 i_ras = (-1, 1.86265e-09, -7.45058e-09) j_ras = (-1.49012e-08, -2.67755e-09, -1) k_ras = (-1.86265e-09, 1, -3.14321e-09) changing data type from uchar to float (noscale = 0)... writing to ./tmp.mri_nu_correct.mni.9713/nu0.mnc... -------------------------------------------------------- Iteration 1 Mon Sep 11 09:48:43 CEST 2017 nu_correct -clobber ./tmp.mri_nu_correct.mni.9713/nu0.mnc ./tmp.mri_nu_correct.mni.9713/nu1.mnc -tmpdir ./tmp.mri_nu_correct.mni.9713/0/ -iterations 1000 -distance 50 [gc@lugh.fisica.uniud.it:/home/gc/study/recon-all/400614bash/mri/] [2017-09-11 09:48:44] running: /usr/local/freesurfer/mni/bin/nu_estimate_np_and_em -parzen -log -sharpen 0.15 0.01 -iterations 1000 -stop 0.001 -shrink 4 -auto_mask -nonotify -b_spline 1.0e-7 -distance 50 -quiet -execute -clobber -nokeeptmp -tmpdir ./tmp.mri_nu_correct.mni.9713/0/ ./tmp.mri_nu_correct.mni.9713/nu0.mnc ./tmp.mri_nu_correct.mni.9713/nu1.imp Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Number of iterations: 81 CV of field change: 0.000954592 mri_binarize --i ./tmp.mri_nu_correct.mni.9713/nu1.mnc --min -1 --o ./tmp.mri_nu_correct.mni.9713/ones.mgz $Id: mri_binarize.c,v 1.43 2016/06/09 20:46:21 greve Exp $ cwd /home/gc/study/recon-all/400614bash/mri cmdline mri_binarize.bin --i ./tmp.mri_nu_correct.mni.9713/nu1.mnc --min -1 --o ./tmp.mri_nu_correct.mni.9713/ones.mgz sysname Linux hostname lugh.fisica.uniud.it machine x86_64 user gc input ./tmp.mri_nu_correct.mni.9713/nu1.mnc frame 0 nErode3d 0 nErode2d 0 output ./tmp.mri_nu_correct.mni.9713/ones.mgz Binarizing based on threshold min -1 max +infinity binval 1 binvalnot 0 fstart = 0, fend = 0, nframes = 1 Found 16777216 values in range Counting number of voxels in first frame Found 16777216 voxels in final mask Count: 16777216 16777216.000000 16777216 100.000000 mri_binarize done mri_segstats --id 1 --seg ./tmp.mri_nu_correct.mni.9713/ones.mgz --i orig.mgz --sum ./tmp.mri_nu_correct.mni.9713/sum.junk --avgwf ./tmp.mri_nu_correct.mni.9713/input.mean.dat $Id: mri_segstats.c,v 1.121 2016/05/31 17:27:11 greve Exp $ cwd cmdline mri_segstats --id 1 --seg ./tmp.mri_nu_correct.mni.9713/ones.mgz --i orig.mgz --sum ./tmp.mri_nu_correct.mni.9713/sum.junk --avgwf ./tmp.mri_nu_correct.mni.9713/input.mean.dat sysname Linux hostname lugh.fisica.uniud.it machine x86_64 user gc UseRobust 0 Loading ./tmp.mri_nu_correct.mni.9713/ones.mgz Loading orig.mgz Voxel Volume is 1 mm^3 Generating list of segmentation ids Found 1 segmentations Computing statistics for each segmentation Reporting on 1 segmentations Using PrintSegStat Computing spatial average of each frame 0 Writing to ./tmp.mri_nu_correct.mni.9713/input.mean.dat mri_segstats done mri_segstats --id 1 --seg ./tmp.mri_nu_correct.mni.9713/ones.mgz --i ./tmp.mri_nu_correct.mni.9713/nu1.mnc --sum ./tmp.mri_nu_correct.mni.9713/sum.junk --avgwf ./tmp.mri_nu_correct.mni.9713/output.mean.dat $Id: mri_segstats.c,v 1.121 2016/05/31 17:27:11 greve Exp $ cwd cmdline mri_segstats --id 1 --seg ./tmp.mri_nu_correct.mni.9713/ones.mgz --i ./tmp.mri_nu_correct.mni.9713/nu1.mnc --sum ./tmp.mri_nu_correct.mni.9713/sum.junk --avgwf ./tmp.mri_nu_correct.mni.9713/output.mean.dat sysname Linux hostname lugh.fisica.uniud.it machine x86_64 user gc UseRobust 0 Loading ./tmp.mri_nu_correct.mni.9713/ones.mgz Loading ./tmp.mri_nu_correct.mni.9713/nu1.mnc Voxel Volume is 1 mm^3 Generating list of segmentation ids Found 1 segmentations Computing statistics for each segmentation Reporting on 1 segmentations Using PrintSegStat Computing spatial average of each frame 0 Writing to ./tmp.mri_nu_correct.mni.9713/output.mean.dat mri_segstats done mris_calc -o ./tmp.mri_nu_correct.mni.9713/nu1.mnc ./tmp.mri_nu_correct.mni.9713/nu1.mnc mul .78721245312251693599 Saving result to './tmp.mri_nu_correct.mni.9713/nu1.mnc' (type = MINC ) [ ok ] mri_convert ./tmp.mri_nu_correct.mni.9713/nu1.mnc nu.mgz --like orig.mgz mri_convert.bin ./tmp.mri_nu_correct.mni.9713/nu1.mnc nu.mgz --like orig.mgz $Id: mri_convert.c,v 1.226 2016/02/26 16:15:24 mreuter Exp $ reading from ./tmp.mri_nu_correct.mni.9713/nu1.mnc... TR=0.00, TE=0.00, TI=0.00, flip angle=0.00 i_ras = (-1, 1.86265e-09, -7.45058e-09) j_ras = (-1.49012e-08, -2.67755e-09, -1) k_ras = (-1.86265e-09, 1, -3.14321e-09) INFO: transform src into the like-volume: orig.mgz writing to nu.mgz... mri_make_uchar nu.mgz transforms/talairach.xfm nu.mgz type change took 0 minutes and 9 seconds. mapping ( 7, 166) to ( 3, 110) Mon Sep 11 09:50:41 CEST 2017 mri_nu_correct.mni done mri_add_xform_to_header -c /home/gc/study/recon-all/400614bash/mri/transforms/talairach.xfm nu.mgz nu.mgz INFO: extension is mgz #-------------------------------------------- #@# Intensity Normalization Mon Sep 11 09:50:41 CEST 2017 /home/gc/study/recon-all/400614bash/mri mri_normalize -g 1 -mprage nu.mgz T1.mgz using max gradient = 1.000 assuming input volume is MGH (Van der Kouwe) MP-RAGE reading from nu.mgz... normalizing image... talairach transform 1.09177 -0.02783 -0.10195 -1.30971; 0.04673 0.97076 0.20972 -27.93497; 0.07529 -0.17263 1.10550 -15.31982; 0.00000 0.00000 0.00000 1.00000; processing without aseg, no1d=0 MRInormInit(): INFO: Modifying talairach volume c_(r,a,s) based on average_305 MRInormalize(): MRIsplineNormalize(): npeaks = 15 Starting OpenSpline(): npoints = 15 building Voronoi diagram... performing soap bubble smoothing, sigma = 8... Iterating 2 times --------------------------------- 3d normalization pass 1 of 2 white matter peak found at 110 white matter peak found at 110 gm peak at 86 (86), valley at 50 (50) csf peak at 43, setting threshold to 71 building Voronoi diagram... performing soap bubble smoothing, sigma = 8... --------------------------------- 3d normalization pass 2 of 2 white matter peak found at 110 white matter peak found at 110 gm peak at 83 (83), valley at 49 (49) csf peak at 42, setting threshold to 69 building Voronoi diagram... performing soap bubble smoothing, sigma = 8... Done iterating --------------------------------- writing output to T1.mgz 3D bias adjustment took 2 minutes and 49 seconds. #-------------------------------------------- #@# Skull Stripping Mon Sep 11 09:53:32 CEST 2017 /home/gc/study/recon-all/400614bash/mri mri_em_register -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_em_register.skull.dat -skull nu.mgz /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta aligning to atlas containing skull, setting unknown_nbr_spacing = 5 == Number of threads available to mri_em_register for OpenMP = 1 == reading 1 input volumes... logging results to talairach_with_skull.log reading '/usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca'... average std = 22.9 using min determinant for regularization = 52.6 0 singular and 9002 ill-conditioned covariance matrices regularized reading 'nu.mgz'... freeing gibbs priors...done. accounting for voxel sizes in initial transform bounding unknown intensity as < 8.7 or > 569.1 total sample mean = 77.6 (1399 zeros) ************************************************ spacing=8, using 3243 sample points, tol=1.00e-05... ************************************************ register_mri: find_optimal_transform find_optimal_transform: nsamples 3243, passno 0, spacing 8 resetting wm mean[0]: 100 --> 108 resetting gm mean[0]: 61 --> 61 input volume #1 is the most T1-like using real data threshold=30.0 skull bounding box = (51, 24, 13) --> (205, 211, 219) using (102, 86, 116) as brain centroid... mean wm in atlas = 108, using box (83,63,91) --> (120, 109,141) to find MRI wm before smoothing, mri peak at 107 robust fit to distribution - 106 +- 4.4 after smoothing, mri peak at 107, scaling input intensities by 1.009 scaling channel 0 by 1.00935 initial log_p = -4.507 ************************************************ First Search limited to translation only. ************************************************ max log p = -4.482771 @ (-9.091, 9.091, -9.091) max log p = -4.384898 @ (13.636, 4.545, 4.545) max log p = -4.366463 @ (-2.273, -2.273, -2.273) max log p = -4.352884 @ (-3.409, -1.136, 1.136) max log p = -4.338823 @ (0.568, -1.705, -1.705) max log p = -4.338823 @ (0.000, 0.000, 0.000) Found translation: (-0.6, 8.5, -7.4): log p = -4.339 **************************************** Nine parameter search. iteration 0 nscales = 0 ... **************************************** Result so far: scale 1.000: max_log_p=-4.205, old_max_log_p =-4.339 (thresh=-4.3) 1.06375 0.00000 0.00000 -8.56520; 0.00000 1.13509 0.16902 -14.65745; 0.00000 -0.11161 0.99651 9.90158; 0.00000 0.00000 0.00000 1.00000; **************************************** Nine parameter search. iteration 1 nscales = 0 ... **************************************** Result so far: scale 1.000: max_log_p=-4.205, old_max_log_p =-4.205 (thresh=-4.2) 1.06375 0.00000 0.00000 -8.56520; 0.00000 1.13509 0.16902 -14.65745; 0.00000 -0.11161 0.99651 9.90158; 0.00000 0.00000 0.00000 1.00000; reducing scale to 0.2500 **************************************** Nine parameter search. iteration 2 nscales = 1 ... **************************************** Result so far: scale 0.250: max_log_p=-4.167, old_max_log_p =-4.205 (thresh=-4.2) 1.08370 0.00000 0.00000 -11.06720; 0.00000 1.13814 0.13632 -13.14113; 0.00000 -0.07442 1.00151 6.57659; 0.00000 0.00000 0.00000 1.00000; **************************************** Nine parameter search. iteration 3 nscales = 1 ... **************************************** Result so far: scale 0.250: max_log_p=-4.161, old_max_log_p =-4.167 (thresh=-4.2) 1.08100 -0.04732 0.05361 -15.10323; 0.03211 1.06839 0.18583 -19.38365; -0.06627 -0.14648 0.98878 23.33018; 0.00000 0.00000 0.00000 1.00000; **************************************** Nine parameter search. iteration 4 nscales = 1 ... **************************************** Result so far: scale 0.250: max_log_p=-4.161, old_max_log_p =-4.161 (thresh=-4.2) 1.08100 -0.04732 0.05361 -15.10323; 0.03211 1.06839 0.18583 -19.38365; -0.06627 -0.14648 0.98878 23.33018; 0.00000 0.00000 0.00000 1.00000; reducing scale to 0.0625 **************************************** Nine parameter search. iteration 5 nscales = 2 ... **************************************** Result so far: scale 0.062: max_log_p=-4.134, old_max_log_p =-4.161 (thresh=-4.2) 1.08507 -0.06262 0.03450 -11.46743; 0.04935 1.06502 0.19430 -21.69804; -0.04904 -0.15612 0.98913 22.28783; 0.00000 0.00000 0.00000 1.00000; **************************************** Nine parameter search. iteration 6 nscales = 2 ... **************************************** Result so far: scale 0.062: max_log_p=-4.133, old_max_log_p =-4.134 (thresh=-4.1) 1.08507 -0.06262 0.03450 -11.46743; 0.04941 1.06626 0.19453 -21.89007; -0.04898 -0.15594 0.98797 22.39170; 0.00000 0.00000 0.00000 1.00000; min search scale 0.025000 reached *********************************************** Computing MAP estimate using 3243 samples... *********************************************** dt = 5.00e-06, momentum=0.80, tol=1.00e-05 l_intensity = 1.0000 Aligning input volume to GCA... Transform matrix 1.08507 -0.06262 0.03450 -11.46743; 0.04941 1.06626 0.19453 -21.89007; -0.04898 -0.15594 0.98797 22.39170; 0.00000 0.00000 0.00000 1.00000; nsamples 3243 Quasinewton: input matrix 1.08507 -0.06262 0.03450 -11.46743; 0.04941 1.06626 0.19453 -21.89007; -0.04898 -0.15594 0.98797 22.39170; 0.00000 0.00000 0.00000 1.00000; outof QuasiNewtonEMA: 009: -log(p) = -0.0 tol 0.000010 Resulting transform: 1.08507 -0.06262 0.03450 -11.46743; 0.04941 1.06626 0.19453 -21.89007; -0.04898 -0.15594 0.98797 22.39170; 0.00000 0.00000 0.00000 1.00000; pass 1, spacing 8: log(p) = -4.133 (old=-4.507) transform before final EM align: 1.08507 -0.06262 0.03450 -11.46743; 0.04941 1.06626 0.19453 -21.89007; -0.04898 -0.15594 0.98797 22.39170; 0.00000 0.00000 0.00000 1.00000; ************************************************** EM alignment process ... Computing final MAP estimate using 364799 samples. ************************************************** dt = 5.00e-06, momentum=0.80, tol=1.00e-07 l_intensity = 1.0000 Aligning input volume to GCA... Transform matrix 1.08507 -0.06262 0.03450 -11.46743; 0.04941 1.06626 0.19453 -21.89007; -0.04898 -0.15594 0.98797 22.39170; 0.00000 0.00000 0.00000 1.00000; nsamples 364799 Quasinewton: input matrix 1.08507 -0.06262 0.03450 -11.46743; 0.04941 1.06626 0.19453 -21.89007; -0.04898 -0.15594 0.98797 22.39170; 0.00000 0.00000 0.00000 1.00000; outof QuasiNewtonEMA: 011: -log(p) = 4.5 tol 0.000000 final transform: 1.08507 -0.06262 0.03450 -11.46743; 0.04941 1.06626 0.19453 -21.89007; -0.04898 -0.15594 0.98797 22.39170; 0.00000 0.00000 0.00000 1.00000; writing output transformation to transforms/talairach_with_skull.lta... mri_em_register utimesec 1174.313477 mri_em_register stimesec 0.820875 mri_em_register ru_maxrss 609776 mri_em_register ru_ixrss 0 mri_em_register ru_idrss 0 mri_em_register ru_isrss 0 mri_em_register ru_minflt 157311 mri_em_register ru_majflt 0 mri_em_register ru_nswap 0 mri_em_register ru_inblock 146504 mri_em_register ru_oublock 24 mri_em_register ru_msgsnd 0 mri_em_register ru_msgrcv 0 mri_em_register ru_nsignals 0 mri_em_register ru_nvcsw 56 mri_em_register ru_nivcsw 121147 registration took 19 minutes and 38 seconds. mri_watershed -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_watershed.dat -brain_atlas /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta -h 5 orig.mgz brainmask_orig_PFH5.auto.mgz mri_watershed -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_watershed.dat -brain_atlas /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta -h 10 orig.mgz brainmask_orig_PFH10.auto.mgz mri_watershed -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_watershed.dat -brain_atlas /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta -h 20 orig.mgz brainmask_orig_PFH20.auto.mgz mri_watershed -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_watershed.dat -brain_atlas /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta -h 30 orig.mgz brainmask_orig_PFH30.auto.mgz mri_watershed -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_watershed.dat -brain_atlas /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta -h 5 orig_nu.mgz brainmask_orig_nu_PFH5.auto.mgz mri_watershed -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_watershed.dat -brain_atlas /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta -h 10 orig_nu.mgz brainmask_orig_nu_PFH10.auto.mgz mri_watershed -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_watershed.dat -brain_atlas /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta -h 20 orig_nu.mgz brainmask_orig_nu_PFH20.auto.mgz mri_watershed -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_watershed.dat -brain_atlas /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta -h 30 orig_nu.mgz brainmask_orig_nu_PFH30.auto.mgz mri_watershed -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_watershed.dat -brain_atlas /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta -h 5 T1.mgz brainmask_T1_PFH5.auto.mgz mri_watershed -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_watershed.dat -brain_atlas /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta -h 10 T1.mgz brainmask_T1_PFH10.auto.mgz mri_watershed -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_watershed.dat -brain_atlas /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta -h 20 T1.mgz brainmask_T1_PFH20.auto.mgz mri_watershed -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_watershed.dat -brain_atlas /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta -h 30 T1.mgz brainmask_T1_PFH30.auto.mgz mri_watershed -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_watershed.dat -brain_atlas /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta -h 5 orig.mgz brainmask_orig_PFH5.auto.mgz Mode: Use the information of atlas (default parms, --help for details) Mode: Preflooding height manually specified ********************************************************* The input file is orig.mgz The output file is brainmask_orig_PFH5.auto.mgz Weighting the input with atlas information before watershed *************************WATERSHED************************** Sorting... first estimation of the COG coord: x=127 y=122 z=109 r=74 first estimation of the main basin volume: 1761353 voxels Looking for seedpoints 2 found in the cerebellum 18 found in the rest of the brain global maximum in x=97, y=106, z=89, Imax=255 CSF=23, WM_intensity=215, WM_VARIANCE=8 WM_MIN=186, WM_HALF_MIN=198, WM_HALF_MAX=224, WM_MAX=233 preflooding height equal to 5 percent done. Analyze... main basin size=9324384677 voxels, voxel volume =1.000 = 9324384677 mmm3 = 9324384.256 cm3 done. PostAnalyze...Basin Prior 562 basins merged thanks to atlas ambiguous basin, merged: at least 17 ambiguous voxels; size: 4913 voxels ***** 1 basin(s) merged in 2 iteration(s) ***** 4913 voxel(s) added to the main basin done. Weighting the input with prior template ****************TEMPLATE DEFORMATION**************** second estimation of the COG coord: x=127,y=105, z=106, r=10559 iterations ^^^^^^^^ couldn't find WM with original limits - expanding ^^^^^^ GLOBAL CSF_MIN=0, CSF_intensity=9, CSF_MAX=27 , nb = 43911 RIGHT_CER CSF_MIN=0, CSF_intensity=9, CSF_MAX=54 , nb = -1036366747 LEFT_CER CSF_MIN=0, CSF_intensity=6, CSF_MAX=37 , nb = -1094237647 RIGHT_BRAIN CSF_MIN=0, CSF_intensity=9, CSF_MAX=26 , nb = 1078980251 LEFT_BRAIN CSF_MIN=0, CSF_intensity=9, CSF_MAX=25 , nb = 1074645700 OTHER CSF_MIN=3, CSF_intensity=48, CSF_MAX=58 , nb = 1076230722 Problem with the least square interpolation in GM_MIN calculation. Problem with the least square interpolation in GM_MIN calculation. Problem with the least square interpolation in GM_MIN calculation. Problem with the least square interpolation in GM_MIN calculation. Problem with the least square interpolation in GM_MIN calculation. CSF_MAX TRANSITION GM_MIN GM GLOBAL before analyzing : 27, 25, 16, 135 after analyzing : 25, 37, 44, 61 RIGHT_CER before analyzing : 54, 42, 0, 161 after analyzing : 42, 43, 44, 72 LEFT_CER before analyzing : 37, 56, 94, 153 after analyzing : 37, 81, 94, 99 RIGHT_BRAIN before analyzing : 26, 24, 17, 135 after analyzing : 24, 37, 44, 61 LEFT_BRAIN before analyzing : 25, 24, 20, 129 after analyzing : 24, 37, 44, 60 OTHER before analyzing : 58, 55, 47, 77 after analyzing : 53, 55, 55, 60 mri_strip_skull: done peeling brain highly tesselated surface with 10242 vertices matching...65 iterations *********************VALIDATION********************* curvature mean = -0.013, std = 0.010 curvature mean = 70.734, std = 7.815 No Rigid alignment: -atlas Mode Off (basic atlas / no registration) before rotation: sse = 1.42, sigma = 2.10 after rotation: sse = 1.42, sigma = 2.10 Localization of inacurate regions: Erosion-Dilation steps the sse mean is 1.42, its var is 1.62 before Erosion-Dilatation 0.00% of inacurate vertices after Erosion-Dilatation 0.00% of inacurate vertices Validation of the shape of the surface done. Scaling of atlas fields onto current surface fields ********FINAL ITERATIVE TEMPLATE DEFORMATION******** Compute Local values csf/gray Fine Segmentation...29 iterations mri_strip_skull: done peeling brain Brain Size = 1701984 voxels, voxel volume = 1.000 mm3 = 1701984 mmm3 = 1701.984 cm3 ****************************** Saving brainmask_orig_PFH5.auto.mgz done mri_watershed utimesec 40.760803 mri_watershed stimesec 0.463929 mri_watershed ru_maxrss 826944 mri_watershed ru_ixrss 0 mri_watershed ru_idrss 0 mri_watershed ru_isrss 0 mri_watershed ru_minflt 209367 mri_watershed ru_majflt 35 mri_watershed ru_nswap 0 mri_watershed ru_inblock 2160 mri_watershed ru_oublock 3448 mri_watershed ru_msgsnd 0 mri_watershed ru_msgrcv 0 mri_watershed ru_nsignals 0 mri_watershed ru_nvcsw 36 mri_watershed ru_nivcsw 4352 mri_watershed done mri_watershed -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_watershed.dat -brain_atlas /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta -h 10 orig.mgz brainmask_orig_PFH10.auto.mgz Mode: Use the information of atlas (default parms, --help for details) Mode: Preflooding height manually specified ********************************************************* The input file is orig.mgz The output file is brainmask_orig_PFH10.auto.mgz Weighting the input with atlas information before watershed *************************WATERSHED************************** Sorting... first estimation of the COG coord: x=127 y=122 z=109 r=74 first estimation of the main basin volume: 1761353 voxels Looking for seedpoints 2 found in the cerebellum 18 found in the rest of the brain global maximum in x=97, y=106, z=89, Imax=255 CSF=23, WM_intensity=215, WM_VARIANCE=8 WM_MIN=186, WM_HALF_MIN=198, WM_HALF_MAX=224, WM_MAX=233 preflooding height equal to 10 percent done. Analyze... main basin size=9726827172 voxels, voxel volume =1.000 = 9726827172 mmm3 = 9726827.520 cm3 done. PostAnalyze...Basin Prior 89 basins merged thanks to atlas ***** 0 basin(s) merged in 1 iteration(s) ***** 0 voxel(s) added to the main basin done. Weighting the input with prior template ****************TEMPLATE DEFORMATION**************** second estimation of the COG coord: x=127,y=104, z=106, r=10558 iterations ^^^^^^^^ couldn't find WM with original limits - expanding ^^^^^^ GLOBAL CSF_MIN=0, CSF_intensity=9, CSF_MAX=25 , nb = 44487 RIGHT_CER CSF_MIN=0, CSF_intensity=11, CSF_MAX=78 , nb = -1036199607 LEFT_CER CSF_MIN=0, CSF_intensity=7, CSF_MAX=47 , nb = -1121876480 RIGHT_BRAIN CSF_MIN=0, CSF_intensity=9, CSF_MAX=24 , nb = 1080326834 LEFT_BRAIN CSF_MIN=0, CSF_intensity=9, CSF_MAX=23 , nb = 1077016106 OTHER CSF_MIN=0, CSF_intensity=43, CSF_MAX=60 , nb = 1071989125 CSF_MAX TRANSITION GM_MIN GM GLOBAL before analyzing : 25, 41, 89, 135 after analyzing : 25, 73, 89, 88 RIGHT_CER before analyzing : 78, 84, 91, 161 after analyzing : 78, 88, 91, 106 LEFT_CER before analyzing : 47, 74, 105, 150 after analyzing : 47, 94, 105, 108 RIGHT_BRAIN before analyzing : 24, 40, 90, 135 after analyzing : 24, 73, 90, 88 LEFT_BRAIN before analyzing : 23, 39, 91, 135 after analyzing : 23, 73, 91, 88 OTHER before analyzing : 60, 54, 46, 75 after analyzing : 49, 54, 54, 59 mri_strip_skull: done peeling brain highly tesselated surface with 10242 vertices matching...60 iterations *********************VALIDATION********************* curvature mean = -0.014, std = 0.010 curvature mean = 69.600, std = 7.630 No Rigid alignment: -atlas Mode Off (basic atlas / no registration) before rotation: sse = 1.39, sigma = 2.13 after rotation: sse = 1.39, sigma = 2.13 Localization of inacurate regions: Erosion-Dilation steps the sse mean is 1.40, its var is 1.62 before Erosion-Dilatation 0.00% of inacurate vertices after Erosion-Dilatation 0.00% of inacurate vertices Validation of the shape of the surface done. Scaling of atlas fields onto current surface fields ********FINAL ITERATIVE TEMPLATE DEFORMATION******** Compute Local values csf/gray Fine Segmentation...44 iterations mri_strip_skull: done peeling brain Brain Size = 1703399 voxels, voxel volume = 1.000 mm3 = 1703399 mmm3 = 1703.399 cm3 ****************************** Saving brainmask_orig_PFH10.auto.mgz done mri_watershed utimesec 44.691205 mri_watershed stimesec 0.428934 mri_watershed ru_maxrss 827352 mri_watershed ru_ixrss 0 mri_watershed ru_idrss 0 mri_watershed ru_isrss 0 mri_watershed ru_minflt 209189 mri_watershed ru_majflt 6 mri_watershed ru_nswap 0 mri_watershed ru_inblock 5896 mri_watershed ru_oublock 3440 mri_watershed ru_msgsnd 0 mri_watershed ru_msgrcv 0 mri_watershed ru_nsignals 0 mri_watershed ru_nvcsw 26 mri_watershed ru_nivcsw 19142 mri_watershed done mri_watershed -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_watershed.dat -brain_atlas /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta -h 20 orig.mgz brainmask_orig_PFH20.auto.mgz Mode: Use the information of atlas (default parms, --help for details) Mode: Preflooding height manually specified ********************************************************* The input file is orig.mgz The output file is brainmask_orig_PFH20.auto.mgz Weighting the input with atlas information before watershed *************************WATERSHED************************** Sorting... first estimation of the COG coord: x=127 y=122 z=109 r=74 first estimation of the main basin volume: 1761353 voxels Looking for seedpoints 2 found in the cerebellum 18 found in the rest of the brain global maximum in x=97, y=106, z=89, Imax=255 CSF=23, WM_intensity=215, WM_VARIANCE=8 WM_MIN=186, WM_HALF_MIN=198, WM_HALF_MAX=224, WM_MAX=233 preflooding height equal to 20 percent done. Analyze... main basin size=9488878049 voxels, voxel volume =1.000 = 9488878049 mmm3 = 9488877.568 cm3 done. PostAnalyze...Basin Prior 7 basins merged thanks to atlas ***** 0 basin(s) merged in 1 iteration(s) ***** 0 voxel(s) added to the main basin done. Weighting the input with prior template ****************TEMPLATE DEFORMATION**************** second estimation of the COG coord: x=127,y=104, z=106, r=10556 iterations ^^^^^^^^ couldn't find WM with original limits - expanding ^^^^^^ GLOBAL CSF_MIN=0, CSF_intensity=9, CSF_MAX=27 , nb = 44775 RIGHT_CER CSF_MIN=0, CSF_intensity=10, CSF_MAX=55 , nb = -1036139682 LEFT_CER CSF_MIN=0, CSF_intensity=9, CSF_MAX=46 , nb = -1078682398 RIGHT_BRAIN CSF_MIN=0, CSF_intensity=9, CSF_MAX=26 , nb = 1079671661 LEFT_BRAIN CSF_MIN=0, CSF_intensity=9, CSF_MAX=25 , nb = 1074870674 OTHER CSF_MIN=0, CSF_intensity=9, CSF_MAX=15 , nb = 1076628598 CSF_MAX TRANSITION GM_MIN GM GLOBAL before analyzing : 27, 43, 90, 142 after analyzing : 27, 74, 90, 91 RIGHT_CER before analyzing : 55, 74, 100, 158 after analyzing : 55, 91, 100, 107 LEFT_CER before analyzing : 46, 70, 103, 153 after analyzing : 46, 92, 103, 107 RIGHT_BRAIN before analyzing : 26, 42, 91, 141 after analyzing : 26, 74, 91, 90 LEFT_BRAIN before analyzing : 25, 43, 93, 135 after analyzing : 25, 76, 93, 90 OTHER before analyzing : 15, 21, 50, 75 after analyzing : 15, 40, 50, 48 mri_strip_skull: done peeling brain highly tesselated surface with 10242 vertices matching...63 iterations *********************VALIDATION********************* curvature mean = -0.014, std = 0.010 curvature mean = 69.650, std = 7.187 No Rigid alignment: -atlas Mode Off (basic atlas / no registration) before rotation: sse = 1.67, sigma = 2.49 after rotation: sse = 1.67, sigma = 2.49 Localization of inacurate regions: Erosion-Dilation steps the sse mean is 1.69, its var is 2.01 before Erosion-Dilatation 0.00% of inacurate vertices after Erosion-Dilatation 0.00% of inacurate vertices Validation of the shape of the surface done. Scaling of atlas fields onto current surface fields ********FINAL ITERATIVE TEMPLATE DEFORMATION******** Compute Local values csf/gray Fine Segmentation...50 iterations mri_strip_skull: done peeling brain Brain Size = 1708472 voxels, voxel volume = 1.000 mm3 = 1708472 mmm3 = 1708.472 cm3 ****************************** Saving brainmask_orig_PFH20.auto.mgz done mri_watershed utimesec 47.091840 mri_watershed stimesec 0.466929 mri_watershed ru_maxrss 826708 mri_watershed ru_ixrss 0 mri_watershed ru_idrss 0 mri_watershed ru_isrss 0 mri_watershed ru_minflt 209356 mri_watershed ru_majflt 37 mri_watershed ru_nswap 0 mri_watershed ru_inblock 2296 mri_watershed ru_oublock 3440 mri_watershed ru_msgsnd 0 mri_watershed ru_msgrcv 0 mri_watershed ru_nsignals 0 mri_watershed ru_nvcsw 37 mri_watershed ru_nivcsw 5875 mri_watershed done mri_watershed -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_watershed.dat -brain_atlas /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta -h 30 orig.mgz brainmask_orig_PFH30.auto.mgz Mode: Use the information of atlas (default parms, --help for details) Mode: Preflooding height manually specified ********************************************************* The input file is orig.mgz The output file is brainmask_orig_PFH30.auto.mgz Weighting the input with atlas information before watershed *************************WATERSHED************************** Sorting... first estimation of the COG coord: x=127 y=122 z=109 r=74 first estimation of the main basin volume: 1761353 voxels Looking for seedpoints 2 found in the cerebellum 18 found in the rest of the brain global maximum in x=97, y=106, z=89, Imax=255 CSF=23, WM_intensity=215, WM_VARIANCE=8 WM_MIN=186, WM_HALF_MIN=198, WM_HALF_MAX=224, WM_MAX=233 preflooding height equal to 30 percent done. Analyze... main basin size=9413225524 voxels, voxel volume =1.000 = 9413225524 mmm3 = 9413225.472 cm3 done. PostAnalyze...Basin Prior 1 basins merged thanks to atlas ***** 0 basin(s) merged in 1 iteration(s) ***** 0 voxel(s) added to the main basin done. Weighting the input with prior template ****************TEMPLATE DEFORMATION**************** second estimation of the COG coord: x=126,y=104, z=106, r=10661 iterations ^^^^^^^^ couldn't find WM with original limits - expanding ^^^^^^ GLOBAL CSF_MIN=0, CSF_intensity=9, CSF_MAX=27 , nb = 44757 RIGHT_CER CSF_MIN=0, CSF_intensity=9, CSF_MAX=65 , nb = -1034965944 LEFT_CER CSF_MIN=0, CSF_intensity=7, CSF_MAX=43 , nb = 1066434800 RIGHT_BRAIN CSF_MIN=0, CSF_intensity=9, CSF_MAX=26 , nb = 1082418917 LEFT_BRAIN CSF_MIN=0, CSF_intensity=9, CSF_MAX=25 , nb = 1077311926 OTHER CSF_MIN=0, CSF_intensity=9, CSF_MAX=122 , nb = 1074551727 CSF_MAX TRANSITION GM_MIN GM GLOBAL before analyzing : 27, 45, 91, 135 after analyzing : 27, 75, 91, 90 RIGHT_CER before analyzing : 65, 80, 98, 163 after analyzing : 65, 92, 98, 109 LEFT_CER before analyzing : 43, 70, 105, 149 after analyzing : 43, 93, 105, 107 RIGHT_BRAIN before analyzing : 26, 45, 92, 134 after analyzing : 26, 76, 92, 90 LEFT_BRAIN before analyzing : 25, 42, 92, 137 after analyzing : 25, 75, 92, 90 OTHER before analyzing : 122, 56, 34, 73 after analyzing : 37, 56, 56, 60 mri_strip_skull: done peeling brain highly tesselated surface with 10242 vertices matching...64 iterations *********************VALIDATION********************* curvature mean = -0.014, std = 0.010 curvature mean = 69.836, std = 7.109 No Rigid alignment: -atlas Mode Off (basic atlas / no registration) before rotation: sse = 1.75, sigma = 2.55 after rotation: sse = 1.75, sigma = 2.55 Localization of inacurate regions: Erosion-Dilation steps the sse mean is 1.76, its var is 2.05 before Erosion-Dilatation 0.01% of inacurate vertices after Erosion-Dilatation 0.00% of inacurate vertices Validation of the shape of the surface done. Scaling of atlas fields onto current surface fields ********FINAL ITERATIVE TEMPLATE DEFORMATION******** Compute Local values csf/gray Fine Segmentation...46 iterations mri_strip_skull: done peeling brain Brain Size = 1723250 voxels, voxel volume = 1.000 mm3 = 1723250 mmm3 = 1723.250 cm3 ****************************** Saving brainmask_orig_PFH30.auto.mgz done mri_watershed utimesec 46.194977 mri_watershed stimesec 0.525920 mri_watershed ru_maxrss 827248 mri_watershed ru_ixrss 0 mri_watershed ru_idrss 0 mri_watershed ru_isrss 0 mri_watershed ru_minflt 209296 mri_watershed ru_majflt 31 mri_watershed ru_nswap 0 mri_watershed ru_inblock 1936 mri_watershed ru_oublock 3472 mri_watershed ru_msgsnd 0 mri_watershed ru_msgrcv 0 mri_watershed ru_nsignals 0 mri_watershed ru_nvcsw 32 mri_watershed ru_nivcsw 11395 mri_watershed done mri_watershed -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_watershed.dat -brain_atlas /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta -h 5 orig_nu.mgz brainmask_orig_nu_PFH5.auto.mgz Mode: Use the information of atlas (default parms, --help for details) Mode: Preflooding height manually specified ********************************************************* The input file is orig_nu.mgz The output file is brainmask_orig_nu_PFH5.auto.mgz Weighting the input with atlas information before watershed *************************WATERSHED************************** Sorting... first estimation of the COG coord: x=127 y=121 z=109 r=75 first estimation of the main basin volume: 1816499 voxels Looking for seedpoints 2 found in the cerebellum 18 found in the rest of the brain global maximum in x=143, y=68, z=112, Imax=255 CSF=21, WM_intensity=177, WM_VARIANCE=5 WM_MIN=167, WM_HALF_MIN=174, WM_HALF_MAX=181, WM_MAX=185 preflooding height equal to 5 percent done. Analyze... main basin size=9240703475 voxels, voxel volume =1.000 = 9240703475 mmm3 = 9240702.976 cm3 done. PostAnalyze...Basin Prior 708 basins merged thanks to atlas ***** 0 basin(s) merged in 1 iteration(s) ***** 0 voxel(s) added to the main basin done. Weighting the input with prior template ****************TEMPLATE DEFORMATION**************** second estimation of the COG coord: x=127,y=105, z=106, r=10467 iterations ^^^^^^^^ couldn't find WM with original limits - expanding ^^^^^^ GLOBAL CSF_MIN=0, CSF_intensity=9, CSF_MAX=35 , nb = 42615 RIGHT_CER CSF_MIN=1, CSF_intensity=9, CSF_MAX=32 , nb = -1036362059 LEFT_CER CSF_MIN=0, CSF_intensity=8, CSF_MAX=37 , nb = -1090957110 RIGHT_BRAIN CSF_MIN=0, CSF_intensity=9, CSF_MAX=36 , nb = 1077875533 LEFT_BRAIN CSF_MIN=0, CSF_intensity=10, CSF_MAX=34 , nb = 1075731422 OTHER CSF_MIN=5, CSF_intensity=41, CSF_MAX=55 , nb = 1075371020 Problem with the least square interpolation in GM_MIN calculation. Problem with the least square interpolation in GM_MIN calculation. Problem with the least square interpolation in GM_MIN calculation. Problem with the least square interpolation in GM_MIN calculation. Problem with the least square interpolation in GM_MIN calculation. (2) Problem with the least square interpolation in GM_MIN calculation. CSF_MAX TRANSITION GM_MIN GM GLOBAL before analyzing : 35, 30, 7, 135 after analyzing : 30, 36, 39, 60 RIGHT_CER before analyzing : 32, 30, 29, 67 after analyzing : 30, 36, 39, 43 LEFT_CER before analyzing : 37, 32, 26, 71 after analyzing : 32, 36, 39, 44 RIGHT_BRAIN before analyzing : 36, 31, 10, 129 after analyzing : 31, 36, 39, 59 LEFT_BRAIN before analyzing : 34, 30, 9, 139 after analyzing : 30, 36, 39, 61 OTHER before analyzing : 55, 22, 0, 9 after analyzing : 22, 33, 39, 34 mri_strip_skull: done peeling brain highly tesselated surface with 10242 vertices matching...67 iterations *********************VALIDATION********************* curvature mean = -0.013, std = 0.010 curvature mean = 71.213, std = 7.764 No Rigid alignment: -atlas Mode Off (basic atlas / no registration) before rotation: sse = 1.45, sigma = 2.38 after rotation: sse = 1.45, sigma = 2.38 Localization of inacurate regions: Erosion-Dilation steps the sse mean is 1.46, its var is 1.94 before Erosion-Dilatation 0.00% of inacurate vertices after Erosion-Dilatation 0.00% of inacurate vertices Validation of the shape of the surface done. Scaling of atlas fields onto current surface fields ********FINAL ITERATIVE TEMPLATE DEFORMATION******** Compute Local values csf/gray Fine Segmentation...27 iterations mri_strip_skull: done peeling brain Brain Size = 1701799 voxels, voxel volume = 1.000 mm3 = 1701799 mmm3 = 1701.799 cm3 ****************************** Saving brainmask_orig_nu_PFH5.auto.mgz done mri_watershed utimesec 39.259031 mri_watershed stimesec 0.428934 mri_watershed ru_maxrss 827328 mri_watershed ru_ixrss 0 mri_watershed ru_idrss 0 mri_watershed ru_isrss 0 mri_watershed ru_minflt 209184 mri_watershed ru_majflt 3 mri_watershed ru_nswap 0 mri_watershed ru_inblock 952 mri_watershed ru_oublock 3312 mri_watershed ru_msgsnd 0 mri_watershed ru_msgrcv 0 mri_watershed ru_nsignals 0 mri_watershed ru_nvcsw 9 mri_watershed ru_nivcsw 4483 mri_watershed done mri_watershed -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_watershed.dat -brain_atlas /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta -h 10 orig_nu.mgz brainmask_orig_nu_PFH10.auto.mgz Mode: Use the information of atlas (default parms, --help for details) Mode: Preflooding height manually specified ********************************************************* The input file is orig_nu.mgz The output file is brainmask_orig_nu_PFH10.auto.mgz Weighting the input with atlas information before watershed *************************WATERSHED************************** Sorting... first estimation of the COG coord: x=127 y=121 z=109 r=75 first estimation of the main basin volume: 1816499 voxels Looking for seedpoints 2 found in the cerebellum 18 found in the rest of the brain global maximum in x=143, y=68, z=112, Imax=255 CSF=21, WM_intensity=177, WM_VARIANCE=5 WM_MIN=167, WM_HALF_MIN=174, WM_HALF_MAX=181, WM_MAX=185 preflooding height equal to 10 percent done. Analyze... main basin size=9731280143 voxels, voxel volume =1.000 = 9731280143 mmm3 = 9731279.872 cm3 done. PostAnalyze...Basin Prior 106 basins merged thanks to atlas ***** 0 basin(s) merged in 1 iteration(s) ***** 0 voxel(s) added to the main basin done. Weighting the input with prior template ****************TEMPLATE DEFORMATION**************** second estimation of the COG coord: x=127,y=106, z=105, r=10562 iterations ^^^^^^^^ couldn't find WM with original limits - expanding ^^^^^^ GLOBAL CSF_MIN=0, CSF_intensity=9, CSF_MAX=35 , nb = 42363 RIGHT_CER CSF_MIN=1, CSF_intensity=9, CSF_MAX=59 , nb = -1035961963 LEFT_CER CSF_MIN=0, CSF_intensity=7, CSF_MAX=102 , nb = -1078041262 RIGHT_BRAIN CSF_MIN=1, CSF_intensity=9, CSF_MAX=35 , nb = 1077574428 LEFT_BRAIN CSF_MIN=0, CSF_intensity=14, CSF_MAX=33 , nb = 1076120756 OTHER CSF_MIN=4, CSF_intensity=32, CSF_MAX=39 , nb = 1075692061 Problem with the least square interpolation in GM_MIN calculation. (2) Problem with the least square interpolation in GM_MIN calculation. CSF_MAX TRANSITION GM_MIN GM GLOBAL before analyzing : 35, 64, 103, 136 after analyzing : 35, 90, 103, 101 RIGHT_CER before analyzing : 59, 67, 79, 149 after analyzing : 59, 75, 79, 93 LEFT_CER before analyzing : 102, 88, 80, 145 after analyzing : 52, 88, 88, 102 RIGHT_BRAIN before analyzing : 35, 65, 104, 136 after analyzing : 35, 91, 104, 102 LEFT_BRAIN before analyzing : 33, 58, 104, 137 after analyzing : 33, 88, 104, 100 OTHER before analyzing : 39, 22, 0, 9 after analyzing : 22, 33, 39, 34 mri_strip_skull: done peeling brain highly tesselated surface with 10242 vertices matching...67 iterations *********************VALIDATION********************* curvature mean = -0.014, std = 0.010 curvature mean = 69.403, std = 7.549 No Rigid alignment: -atlas Mode Off (basic atlas / no registration) before rotation: sse = 1.48, sigma = 2.27 after rotation: sse = 1.48, sigma = 2.27 Localization of inacurate regions: Erosion-Dilation steps the sse mean is 1.48, its var is 1.70 before Erosion-Dilatation 0.00% of inacurate vertices after Erosion-Dilatation 0.00% of inacurate vertices Validation of the shape of the surface done. Scaling of atlas fields onto current surface fields ********FINAL ITERATIVE TEMPLATE DEFORMATION******** Compute Local values csf/gray Fine Segmentation...39 iterations mri_strip_skull: done peeling brain Brain Size = 1697209 voxels, voxel volume = 1.000 mm3 = 1697209 mmm3 = 1697.209 cm3 ****************************** Saving brainmask_orig_nu_PFH10.auto.mgz done mri_watershed utimesec 44.073299 mri_watershed stimesec 0.442932 mri_watershed ru_maxrss 827324 mri_watershed ru_ixrss 0 mri_watershed ru_idrss 0 mri_watershed ru_isrss 0 mri_watershed ru_minflt 209186 mri_watershed ru_majflt 0 mri_watershed ru_nswap 0 mri_watershed ru_inblock 0 mri_watershed ru_oublock 3296 mri_watershed ru_msgsnd 0 mri_watershed ru_msgrcv 0 mri_watershed ru_nsignals 0 mri_watershed ru_nvcsw 0 mri_watershed ru_nivcsw 5209 mri_watershed done mri_watershed -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_watershed.dat -brain_atlas /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta -h 20 orig_nu.mgz brainmask_orig_nu_PFH20.auto.mgz Mode: Use the information of atlas (default parms, --help for details) Mode: Preflooding height manually specified ********************************************************* The input file is orig_nu.mgz The output file is brainmask_orig_nu_PFH20.auto.mgz Weighting the input with atlas information before watershed *************************WATERSHED************************** Sorting... first estimation of the COG coord: x=127 y=121 z=109 r=75 first estimation of the main basin volume: 1816499 voxels Looking for seedpoints 2 found in the cerebellum 18 found in the rest of the brain global maximum in x=143, y=68, z=112, Imax=255 CSF=21, WM_intensity=177, WM_VARIANCE=5 WM_MIN=167, WM_HALF_MIN=174, WM_HALF_MAX=181, WM_MAX=185 preflooding height equal to 20 percent done. Analyze... main basin size=9798014416 voxels, voxel volume =1.000 = 9798014416 mmm3 = 9798013.952 cm3 done. PostAnalyze...Basin Prior 12 basins merged thanks to atlas ***** 0 basin(s) merged in 1 iteration(s) ***** 0 voxel(s) added to the main basin done. Weighting the input with prior template ****************TEMPLATE DEFORMATION**************** second estimation of the COG coord: x=127,y=104, z=105, r=10557 iterations ^^^^^^^^ couldn't find WM with original limits - expanding ^^^^^^ GLOBAL CSF_MIN=1, CSF_intensity=9, CSF_MAX=36 , nb = 43677 RIGHT_CER CSF_MIN=0, CSF_intensity=11, CSF_MAX=68 , nb = -1036017839 LEFT_CER CSF_MIN=1, CSF_intensity=9, CSF_MAX=64 , nb = -1078581735 RIGHT_BRAIN CSF_MIN=1, CSF_intensity=9, CSF_MAX=36 , nb = 1078650248 LEFT_BRAIN CSF_MIN=0, CSF_intensity=14, CSF_MAX=33 , nb = 1074765066 OTHER CSF_MIN=2, CSF_intensity=38, CSF_MAX=57 , nb = 1076085574 Problem with the least square interpolation in GM_MIN calculation. (2) Problem with the least square interpolation in GM_MIN calculation. CSF_MAX TRANSITION GM_MIN GM GLOBAL before analyzing : 36, 66, 104, 138 after analyzing : 36, 91, 104, 102 RIGHT_CER before analyzing : 68, 90, 108, 152 after analyzing : 68, 102, 108, 114 LEFT_CER before analyzing : 64, 45, 36, 64 after analyzing : 35, 45, 45, 49 RIGHT_BRAIN before analyzing : 36, 67, 104, 136 after analyzing : 36, 91, 104, 102 LEFT_BRAIN before analyzing : 33, 60, 106, 137 after analyzing : 33, 90, 106, 101 OTHER before analyzing : 57, 19, 0, 9 after analyzing : 19, 32, 39, 33 mri_strip_skull: done peeling brain highly tesselated surface with 10242 vertices matching...65 iterations *********************VALIDATION********************* curvature mean = -0.013, std = 0.010 curvature mean = 69.559, std = 7.229 No Rigid alignment: -atlas Mode Off (basic atlas / no registration) before rotation: sse = 1.69, sigma = 2.63 after rotation: sse = 1.69, sigma = 2.63 Localization of inacurate regions: Erosion-Dilation steps the sse mean is 1.71, its var is 2.11 before Erosion-Dilatation 0.00% of inacurate vertices after Erosion-Dilatation 0.00% of inacurate vertices Validation of the shape of the surface done. Scaling of atlas fields onto current surface fields ********FINAL ITERATIVE TEMPLATE DEFORMATION******** Compute Local values csf/gray Fine Segmentation...44 iterations mri_strip_skull: done peeling brain Brain Size = 1708490 voxels, voxel volume = 1.000 mm3 = 1708490 mmm3 = 1708.490 cm3 ****************************** Saving brainmask_orig_nu_PFH20.auto.mgz done mri_watershed utimesec 44.796189 mri_watershed stimesec 0.414936 mri_watershed ru_maxrss 826984 mri_watershed ru_ixrss 0 mri_watershed ru_idrss 0 mri_watershed ru_isrss 0 mri_watershed ru_minflt 209275 mri_watershed ru_majflt 16 mri_watershed ru_nswap 0 mri_watershed ru_inblock 1008 mri_watershed ru_oublock 3344 mri_watershed ru_msgsnd 0 mri_watershed ru_msgrcv 0 mri_watershed ru_nsignals 0 mri_watershed ru_nvcsw 17 mri_watershed ru_nivcsw 6021 mri_watershed done mri_watershed -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_watershed.dat -brain_atlas /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta -h 30 orig_nu.mgz brainmask_orig_nu_PFH30.auto.mgz Mode: Use the information of atlas (default parms, --help for details) Mode: Preflooding height manually specified ********************************************************* The input file is orig_nu.mgz The output file is brainmask_orig_nu_PFH30.auto.mgz Weighting the input with atlas information before watershed *************************WATERSHED************************** Sorting... first estimation of the COG coord: x=127 y=121 z=109 r=75 first estimation of the main basin volume: 1816499 voxels Looking for seedpoints 2 found in the cerebellum 18 found in the rest of the brain global maximum in x=143, y=68, z=112, Imax=255 CSF=21, WM_intensity=177, WM_VARIANCE=5 WM_MIN=167, WM_HALF_MIN=174, WM_HALF_MAX=181, WM_MAX=185 preflooding height equal to 30 percent done. Analyze... main basin size=9899966072 voxels, voxel volume =1.000 = 9899966072 mmm3 = 9899966.464 cm3 done. PostAnalyze...Basin Prior 0 basins merged thanks to atlas ***** 0 basin(s) merged in 1 iteration(s) ***** 0 voxel(s) added to the main basin done. Weighting the input with prior template ****************TEMPLATE DEFORMATION**************** second estimation of the COG coord: x=127,y=104, z=106, r=10456 iterations ^^^^^^^^ couldn't find WM with original limits - expanding ^^^^^^ (2) Problem with the least square interpolation for CSF_MAX GLOBAL CSF_MIN=1, CSF_intensity=9, CSF_MAX=37 , nb = 43910 RIGHT_CER CSF_MIN=0, CSF_intensity=9, CSF_MAX=62 , nb = -1035415190 LEFT_CER CSF_MIN=0, CSF_intensity=12, CSF_MAX=50 , nb = 1062925631 RIGHT_BRAIN CSF_MIN=1, CSF_intensity=9, CSF_MAX=37 , nb = 1081939136 LEFT_BRAIN CSF_MIN=0, CSF_intensity=14, CSF_MAX=33 , nb = 1077774602 OTHER CSF_MIN=0, CSF_intensity=9, CSF_MAX=59 , nb = 1073009262 CSF_MAX TRANSITION GM_MIN GM GLOBAL before analyzing : 37, 67, 103, 136 after analyzing : 37, 91, 103, 102 RIGHT_CER before analyzing : 62, 88, 109, 151 after analyzing : 62, 102, 109, 114 LEFT_CER before analyzing : 50, 61, 82, 147 after analyzing : 50, 75, 82, 93 RIGHT_BRAIN before analyzing : 37, 70, 105, 134 after analyzing : 37, 93, 105, 103 LEFT_BRAIN before analyzing : 33, 59, 105, 137 after analyzing : 33, 89, 105, 101 OTHER before analyzing : 59, 43, 29, 73 after analyzing : 28, 43, 43, 50 mri_strip_skull: done peeling brain highly tesselated surface with 10242 vertices matching...65 iterations *********************VALIDATION********************* curvature mean = -0.014, std = 0.010 curvature mean = 69.672, std = 7.160 No Rigid alignment: -atlas Mode Off (basic atlas / no registration) before rotation: sse = 1.83, sigma = 2.82 after rotation: sse = 1.83, sigma = 2.82 Localization of inacurate regions: Erosion-Dilation steps the sse mean is 1.90, its var is 2.58 before Erosion-Dilatation 0.06% of inacurate vertices after Erosion-Dilatation 0.00% of inacurate vertices Validation of the shape of the surface done. Scaling of atlas fields onto current surface fields ********FINAL ITERATIVE TEMPLATE DEFORMATION******** Compute Local values csf/gray Fine Segmentation...44 iterations mri_strip_skull: done peeling brain Brain Size = 1718777 voxels, voxel volume = 1.000 mm3 = 1718777 mmm3 = 1718.777 cm3 ****************************** Saving brainmask_orig_nu_PFH30.auto.mgz done mri_watershed utimesec 45.154135 mri_watershed stimesec 0.402938 mri_watershed ru_maxrss 827324 mri_watershed ru_ixrss 0 mri_watershed ru_idrss 0 mri_watershed ru_isrss 0 mri_watershed ru_minflt 209187 mri_watershed ru_majflt 0 mri_watershed ru_nswap 0 mri_watershed ru_inblock 0 mri_watershed ru_oublock 3344 mri_watershed ru_msgsnd 0 mri_watershed ru_msgrcv 0 mri_watershed ru_nsignals 0 mri_watershed ru_nvcsw 0 mri_watershed ru_nivcsw 8172 mri_watershed done mri_watershed -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_watershed.dat -brain_atlas /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta -h 5 T1.mgz brainmask_T1_PFH5.auto.mgz Mode: Use the information of atlas (default parms, --help for details) Mode: Preflooding height manually specified ********************************************************* The input file is T1.mgz The output file is brainmask_T1_PFH5.auto.mgz Weighting the input with atlas information before watershed *************************WATERSHED************************** Sorting... first estimation of the COG coord: x=127 y=121 z=109 r=75 first estimation of the main basin volume: 1798859 voxels Looking for seedpoints 2 found in the cerebellum 18 found in the rest of the brain global maximum in x=110, y=90, z=73, Imax=255 CSF=12, WM_intensity=110, WM_VARIANCE=5 WM_MIN=110, WM_HALF_MIN=110, WM_HALF_MAX=110, WM_MAX=110 preflooding height equal to 5 percent done. Analyze... main basin size=9395772457 voxels, voxel volume =1.000 = 9395772457 mmm3 = 9395772.416 cm3 done. PostAnalyze...Basin Prior 164 basins merged thanks to atlas ***** 0 basin(s) merged in 1 iteration(s) ***** 0 voxel(s) added to the main basin done. Weighting the input with prior template ****************TEMPLATE DEFORMATION**************** second estimation of the COG coord: x=127,y=106, z=106, r=10462 iterations ^^^^^^^^ couldn't find WM with original limits - expanding ^^^^^^ GLOBAL CSF_MIN=0, CSF_intensity=5, CSF_MAX=18 , nb = 42795 RIGHT_CER CSF_MIN=0, CSF_intensity=4, CSF_MAX=28 , nb = -1036166663 LEFT_CER CSF_MIN=1, CSF_intensity=2, CSF_MAX=28 , nb = 1027395102 RIGHT_BRAIN CSF_MIN=0, CSF_intensity=5, CSF_MAX=18 , nb = 1079406441 LEFT_BRAIN CSF_MIN=0, CSF_intensity=5, CSF_MAX=18 , nb = 1075774952 OTHER CSF_MIN=1, CSF_intensity=32, CSF_MAX=38 , nb = 1074906575 Problem with the least square interpolation in GM_MIN calculation. CSF_MAX TRANSITION GM_MIN GM GLOBAL before analyzing : 18, 35, 60, 78 after analyzing : 18, 51, 60, 57 RIGHT_CER before analyzing : 28, 37, 53, 93 after analyzing : 28, 47, 53, 58 LEFT_CER before analyzing : 28, 37, 53, 93 after analyzing : 28, 47, 53, 58 RIGHT_BRAIN before analyzing : 18, 36, 60, 77 after analyzing : 18, 52, 60, 58 LEFT_BRAIN before analyzing : 18, 35, 60, 79 after analyzing : 18, 51, 60, 58 OTHER before analyzing : 38, 34, 24, 39 after analyzing : 33, 34, 34, 35 mri_strip_skull: done peeling brain highly tesselated surface with 10242 vertices matching...64 iterations *********************VALIDATION********************* curvature mean = -0.013, std = 0.011 curvature mean = 69.240, std = 7.848 No Rigid alignment: -atlas Mode Off (basic atlas / no registration) before rotation: sse = 1.28, sigma = 2.04 after rotation: sse = 1.28, sigma = 2.04 Localization of inacurate regions: Erosion-Dilation steps the sse mean is 1.28, its var is 1.52 before Erosion-Dilatation 0.00% of inacurate vertices after Erosion-Dilatation 0.00% of inacurate vertices Validation of the shape of the surface done. Scaling of atlas fields onto current surface fields ********FINAL ITERATIVE TEMPLATE DEFORMATION******** Compute Local values csf/gray Fine Segmentation...45 iterations mri_strip_skull: done peeling brain Brain Size = 1678244 voxels, voxel volume = 1.000 mm3 = 1678244 mmm3 = 1678.244 cm3 ****************************** Saving brainmask_T1_PFH5.auto.mgz done mri_watershed utimesec 44.811187 mri_watershed stimesec 0.417936 mri_watershed ru_maxrss 812608 mri_watershed ru_ixrss 0 mri_watershed ru_idrss 0 mri_watershed ru_isrss 0 mri_watershed ru_minflt 209059 mri_watershed ru_majflt 333 mri_watershed ru_nswap 0 mri_watershed ru_inblock 21056 mri_watershed ru_oublock 2664 mri_watershed ru_msgsnd 0 mri_watershed ru_msgrcv 0 mri_watershed ru_nsignals 0 mri_watershed ru_nvcsw 335 mri_watershed ru_nivcsw 5042 mri_watershed done mri_watershed -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_watershed.dat -brain_atlas /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta -h 10 T1.mgz brainmask_T1_PFH10.auto.mgz Mode: Use the information of atlas (default parms, --help for details) Mode: Preflooding height manually specified ********************************************************* The input file is T1.mgz The output file is brainmask_T1_PFH10.auto.mgz Weighting the input with atlas information before watershed *************************WATERSHED************************** Sorting... first estimation of the COG coord: x=127 y=121 z=109 r=75 first estimation of the main basin volume: 1798859 voxels Looking for seedpoints 2 found in the cerebellum 18 found in the rest of the brain global maximum in x=110, y=90, z=73, Imax=255 CSF=12, WM_intensity=110, WM_VARIANCE=5 WM_MIN=110, WM_HALF_MIN=110, WM_HALF_MAX=110, WM_MAX=110 preflooding height equal to 10 percent done. Analyze... main basin size=9554275616 voxels, voxel volume =1.000 = 9554275616 mmm3 = 9554275.328 cm3 done. PostAnalyze...Basin Prior 34 basins merged thanks to atlas ***** 0 basin(s) merged in 1 iteration(s) ***** 0 voxel(s) added to the main basin done. Weighting the input with prior template ****************TEMPLATE DEFORMATION**************** second estimation of the COG coord: x=126,y=105, z=106, r=10458 iterations ^^^^^^^^ couldn't find WM with original limits - expanding ^^^^^^ GLOBAL CSF_MIN=0, CSF_intensity=5, CSF_MAX=19 , nb = 43731 RIGHT_CER CSF_MIN=0, CSF_intensity=5, CSF_MAX=42 , nb = -1036153982 LEFT_CER CSF_MIN=1, CSF_intensity=2, CSF_MAX=37 , nb = -1088592882 RIGHT_BRAIN CSF_MIN=0, CSF_intensity=5, CSF_MAX=18 , nb = 1080832722 LEFT_BRAIN CSF_MIN=0, CSF_intensity=5, CSF_MAX=17 , nb = 1073299818 OTHER CSF_MIN=1, CSF_intensity=17, CSF_MAX=45 , nb = 1077384996 Problem with the least square interpolation in GM_MIN calculation. CSF_MAX TRANSITION GM_MIN GM GLOBAL before analyzing : 19, 36, 60, 78 after analyzing : 19, 52, 60, 58 RIGHT_CER before analyzing : 42, 42, 44, 94 after analyzing : 42, 43, 44, 55 LEFT_CER before analyzing : 37, 45, 56, 95 after analyzing : 37, 52, 56, 62 RIGHT_BRAIN before analyzing : 18, 34, 59, 78 after analyzing : 18, 50, 59, 57 LEFT_BRAIN before analyzing : 17, 33, 60, 79 after analyzing : 17, 51, 60, 58 OTHER before analyzing : 45, 31, 24, 38 after analyzing : 27, 31, 31, 32 mri_strip_skull: done peeling brain highly tesselated surface with 10242 vertices matching...66 iterations *********************VALIDATION********************* curvature mean = -0.013, std = 0.011 curvature mean = 69.295, std = 7.675 No Rigid alignment: -atlas Mode Off (basic atlas / no registration) before rotation: sse = 1.31, sigma = 2.11 after rotation: sse = 1.31, sigma = 2.11 Localization of inacurate regions: Erosion-Dilation steps the sse mean is 1.31, its var is 1.59 before Erosion-Dilatation 0.00% of inacurate vertices after Erosion-Dilatation 0.00% of inacurate vertices Validation of the shape of the surface done. Scaling of atlas fields onto current surface fields ********FINAL ITERATIVE TEMPLATE DEFORMATION******** Compute Local values csf/gray Fine Segmentation...43 iterations mri_strip_skull: done peeling brain Brain Size = 1677004 voxels, voxel volume = 1.000 mm3 = 1677004 mmm3 = 1677.004 cm3 ****************************** Saving brainmask_T1_PFH10.auto.mgz done mri_watershed utimesec 44.407249 mri_watershed stimesec 0.365944 mri_watershed ru_maxrss 820628 mri_watershed ru_ixrss 0 mri_watershed ru_idrss 0 mri_watershed ru_isrss 0 mri_watershed ru_minflt 207767 mri_watershed ru_majflt 19 mri_watershed ru_nswap 0 mri_watershed ru_inblock 1200 mri_watershed ru_oublock 2664 mri_watershed ru_msgsnd 0 mri_watershed ru_msgrcv 0 mri_watershed ru_nsignals 0 mri_watershed ru_nvcsw 20 mri_watershed ru_nivcsw 31795 mri_watershed done mri_watershed -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_watershed.dat -brain_atlas /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta -h 20 T1.mgz brainmask_T1_PFH20.auto.mgz Mode: Use the information of atlas (default parms, --help for details) Mode: Preflooding height manually specified ********************************************************* The input file is T1.mgz The output file is brainmask_T1_PFH20.auto.mgz Weighting the input with atlas information before watershed *************************WATERSHED************************** Sorting... first estimation of the COG coord: x=127 y=121 z=109 r=75 first estimation of the main basin volume: 1798859 voxels Looking for seedpoints 2 found in the cerebellum 18 found in the rest of the brain global maximum in x=110, y=90, z=73, Imax=255 CSF=12, WM_intensity=110, WM_VARIANCE=5 WM_MIN=110, WM_HALF_MIN=110, WM_HALF_MAX=110, WM_MAX=110 preflooding height equal to 20 percent done. Analyze... main basin size=9890385309 voxels, voxel volume =1.000 = 9890385309 mmm3 = 9890384.896 cm3 done. PostAnalyze...Basin Prior 14 basins merged thanks to atlas ***** 0 basin(s) merged in 1 iteration(s) ***** 0 voxel(s) added to the main basin done. Weighting the input with prior template ****************TEMPLATE DEFORMATION**************** second estimation of the COG coord: x=126,y=104, z=106, r=10457 iterations ^^^^^^^^ couldn't find WM with original limits - expanding ^^^^^^ GLOBAL CSF_MIN=0, CSF_intensity=5, CSF_MAX=20 , nb = 44487 RIGHT_CER CSF_MIN=0, CSF_intensity=4, CSF_MAX=47 , nb = -1035188810 LEFT_CER CSF_MIN=0, CSF_intensity=4, CSF_MAX=39 , nb = 1066911644 RIGHT_BRAIN CSF_MIN=0, CSF_intensity=5, CSF_MAX=19 , nb = 1082663859 LEFT_BRAIN CSF_MIN=0, CSF_intensity=5, CSF_MAX=18 , nb = 1077444290 OTHER CSF_MIN=0, CSF_intensity=18, CSF_MAX=39 , nb = 1071979450 Problem with the least square interpolation in GM_MIN calculation. CSF_MAX TRANSITION GM_MIN GM GLOBAL before analyzing : 20, 36, 58, 78 after analyzing : 20, 50, 58, 57 RIGHT_CER before analyzing : 47, 40, 32, 91 after analyzing : 30, 40, 40, 52 LEFT_CER before analyzing : 39, 45, 53, 92 after analyzing : 39, 50, 53, 60 RIGHT_BRAIN before analyzing : 19, 36, 59, 77 after analyzing : 19, 51, 59, 57 LEFT_BRAIN before analyzing : 18, 35, 60, 79 after analyzing : 18, 51, 60, 58 OTHER before analyzing : 39, 29, 22, 38 after analyzing : 26, 29, 29, 31 mri_strip_skull: done peeling brain highly tesselated surface with 10242 vertices matching...66 iterations *********************VALIDATION********************* curvature mean = -0.014, std = 0.010 curvature mean = 69.661, std = 7.141 No Rigid alignment: -atlas Mode Off (basic atlas / no registration) before rotation: sse = 1.75, sigma = 2.61 after rotation: sse = 1.75, sigma = 2.61 Localization of inacurate regions: Erosion-Dilation steps the sse mean is 1.77, its var is 2.09 before Erosion-Dilatation 0.00% of inacurate vertices after Erosion-Dilatation 0.00% of inacurate vertices Validation of the shape of the surface done. Scaling of atlas fields onto current surface fields ********FINAL ITERATIVE TEMPLATE DEFORMATION******** Compute Local values csf/gray Fine Segmentation...47 iterations mri_strip_skull: done peeling brain Brain Size = 1709897 voxels, voxel volume = 1.000 mm3 = 1709897 mmm3 = 1709.897 cm3 ****************************** Saving brainmask_T1_PFH20.auto.mgz done mri_watershed utimesec 42.299569 mri_watershed stimesec 0.436933 mri_watershed ru_maxrss 813408 mri_watershed ru_ixrss 0 mri_watershed ru_idrss 0 mri_watershed ru_isrss 0 mri_watershed ru_minflt 209205 mri_watershed ru_majflt 228 mri_watershed ru_nswap 0 mri_watershed ru_inblock 14280 mri_watershed ru_oublock 2736 mri_watershed ru_msgsnd 0 mri_watershed ru_msgrcv 0 mri_watershed ru_nsignals 0 mri_watershed ru_nvcsw 230 mri_watershed ru_nivcsw 12471 mri_watershed done mri_watershed -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_watershed.dat -brain_atlas /usr/local/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta -h 30 T1.mgz brainmask_T1_PFH30.auto.mgz Mode: Use the information of atlas (default parms, --help for details) Mode: Preflooding height manually specified ********************************************************* The input file is T1.mgz The output file is brainmask_T1_PFH30.auto.mgz Weighting the input with atlas information before watershed *************************WATERSHED************************** Sorting... first estimation of the COG coord: x=127 y=121 z=109 r=75 first estimation of the main basin volume: 1798859 voxels Looking for seedpoints 2 found in the cerebellum 18 found in the rest of the brain global maximum in x=110, y=90, z=73, Imax=255 CSF=12, WM_intensity=110, WM_VARIANCE=5 WM_MIN=110, WM_HALF_MIN=110, WM_HALF_MAX=110, WM_MAX=110 preflooding height equal to 30 percent done. Analyze... main basin size=9518523353 voxels, voxel volume =1.000 = 9518523353 mmm3 = 9518523.392 cm3 done. PostAnalyze...Basin Prior 14 basins merged thanks to atlas ***** 0 basin(s) merged in 1 iteration(s) ***** 0 voxel(s) added to the main basin done. Weighting the input with prior template ****************TEMPLATE DEFORMATION**************** second estimation of the COG coord: x=127,y=105, z=109, r=10361 iterations ^^^^^^^^ couldn't find WM with original limits - expanding ^^^^^^ GLOBAL CSF_MIN=0, CSF_intensity=5, CSF_MAX=21 , nb = 44162 RIGHT_CER CSF_MIN=0, CSF_intensity=4, CSF_MAX=45 , nb = -1035707524 LEFT_CER CSF_MIN=0, CSF_intensity=4, CSF_MAX=31 , nb = 1078907525 RIGHT_BRAIN CSF_MIN=0, CSF_intensity=5, CSF_MAX=20 , nb = 1079494634 LEFT_BRAIN CSF_MIN=0, CSF_intensity=5, CSF_MAX=19 , nb = 1075476852 OTHER CSF_MIN=0, CSF_intensity=18, CSF_MAX=41 , nb = 1074265725 Problem with the least square interpolation in GM_MIN calculation. CSF_MAX TRANSITION GM_MIN GM GLOBAL before analyzing : 21, 38, 60, 79 after analyzing : 21, 52, 60, 58 RIGHT_CER before analyzing : 45, 48, 52, 94 after analyzing : 45, 50, 52, 61 LEFT_CER before analyzing : 31, 44, 60, 93 after analyzing : 31, 54, 60, 63 RIGHT_BRAIN before analyzing : 20, 39, 61, 77 after analyzing : 20, 53, 61, 59 LEFT_BRAIN before analyzing : 19, 36, 60, 79 after analyzing : 19, 52, 60, 58 OTHER before analyzing : 41, 29, 22, 38 after analyzing : 26, 29, 29, 31 mri_strip_skull: done peeling brain highly tesselated surface with 10242 vertices matching...68 iterations *********************VALIDATION********************* curvature mean = -0.014, std = 0.010 curvature mean = 70.018, std = 7.472 No Rigid alignment: -atlas Mode Off (basic atlas / no registration) before rotation: sse = 1.96, sigma = 3.04 after rotation: sse = 1.96, sigma = 3.04 Localization of inacurate regions: Erosion-Dilation steps the sse mean is 2.00, its var is 2.56 before Erosion-Dilatation 0.09% of inacurate vertices after Erosion-Dilatation 0.00% of inacurate vertices Validation of the shape of the surface done. Scaling of atlas fields onto current surface fields ********FINAL ITERATIVE TEMPLATE DEFORMATION******** Compute Local values csf/gray Fine Segmentation...46 iterations mri_strip_skull: done peeling brain Brain Size = 1736523 voxels, voxel volume = 1.000 mm3 = 1736523 mmm3 = 1736.523 cm3 ****************************** Saving brainmask_T1_PFH30.auto.mgz done mri_watershed utimesec 45.474086 mri_watershed stimesec 0.397939 mri_watershed ru_maxrss 821124 mri_watershed ru_ixrss 0 mri_watershed ru_idrss 0 mri_watershed ru_isrss 0 mri_watershed ru_minflt 210233 mri_watershed ru_majflt 219 mri_watershed ru_nswap 0 mri_watershed ru_inblock 13920 mri_watershed ru_oublock 2768 mri_watershed ru_msgsnd 0 mri_watershed ru_msgrcv 0 mri_watershed ru_nsignals 0 mri_watershed ru_nvcsw 243 mri_watershed ru_nivcsw 5037 mri_watershed done mri_mask T1.mgz brainmask_orig_PFH5.auto.mgz brainmask_orig_PFH5.auto.mgz mri_mask T1.mgz brainmask_orig_PFH10.auto.mgz brainmask_orig_PFH10.auto.mgz mri_mask T1.mgz brainmask_orig_PFH20.auto.mgz brainmask_orig_PFH20.auto.mgz mri_mask T1.mgz brainmask_orig_PFH30.auto.mgz brainmask_orig_PFH30.auto.mgz mri_mask T1.mgz brainmask_orig_PFH5.auto.mgz brainmask_orig_PFH5.auto.mgz DoAbs = 0 Writing masked volume to brainmask_orig_PFH5.auto.mgz...done. mri_mask T1.mgz brainmask_orig_PFH10.auto.mgz brainmask_orig_PFH10.auto.mgz DoAbs = 0 Writing masked volume to brainmask_orig_PFH10.auto.mgz...done. mri_mask T1.mgz brainmask_orig_PFH20.auto.mgz brainmask_orig_PFH20.auto.mgz DoAbs = 0 Writing masked volume to brainmask_orig_PFH20.auto.mgz...done. mri_mask T1.mgz brainmask_orig_PFH30.auto.mgz brainmask_orig_PFH30.auto.mgz DoAbs = 0 Writing masked volume to brainmask_orig_PFH30.auto.mgz...done. mri_log_likelihood -orig T1.mgz brainmask_orig_PFH5.auto.mgz /usr/local/freesurfer/average/RB_all_2016-05-10.vc700.gca transforms/talairach_with_skull.lta valid intensity range = [26, 116] 9786 zero brain voxels -62345 brainmask_orig_PFH5.auto.mgz log_likelihood= -62345 mri_log_likelihood -orig T1.mgz brainmask_orig_PFH10.auto.mgz /usr/local/freesurfer/average/RB_all_2016-05-10.vc700.gca transforms/talairach_with_skull.lta valid intensity range = [26, 116] 9587 zero brain voxels -62278 brainmask_orig_PFH10.auto.mgz log_likelihood= -62278 mri_log_likelihood -orig T1.mgz brainmask_orig_PFH20.auto.mgz /usr/local/freesurfer/average/RB_all_2016-05-10.vc700.gca transforms/talairach_with_skull.lta valid intensity range = [26, 116] 10039 zero brain voxels -62397 brainmask_orig_PFH20.auto.mgz log_likelihood= -62397 mri_log_likelihood -orig T1.mgz brainmask_orig_PFH30.auto.mgz /usr/local/freesurfer/average/RB_all_2016-05-10.vc700.gca transforms/talairach_with_skull.lta valid intensity range = [26, 116] 9511 zero brain voxels -62371 brainmask_orig_PFH30.auto.mgz log_likelihood= -62371 mri_log_likelihood -orig T1.mgz brainmask_orig_nu_PFH5.auto.mgz /usr/local/freesurfer/average/RB_all_2016-05-10.vc700.gca transforms/talairach_with_skull.lta valid intensity range = [26, 116] 9184 zero brain voxels -123826 brainmask_orig_nu_PFH5.auto.mgz log_likelihood= -123826 mri_log_likelihood -orig T1.mgz brainmask_orig_nu_PFH10.auto.mgz /usr/local/freesurfer/average/RB_all_2016-05-10.vc700.gca transforms/talairach_with_skull.lta valid intensity range = [26, 116] 9697 zero brain voxels -123717 brainmask_orig_nu_PFH10.auto.mgz log_likelihood= -123717 mri_log_likelihood -orig T1.mgz brainmask_orig_nu_PFH20.auto.mgz /usr/local/freesurfer/average/RB_all_2016-05-10.vc700.gca transforms/talairach_with_skull.lta valid intensity range = [26, 116] 9963 zero brain voxels -123929 brainmask_orig_nu_PFH20.auto.mgz log_likelihood= -123929 mri_log_likelihood -orig T1.mgz brainmask_orig_nu_PFH30.auto.mgz /usr/local/freesurfer/average/RB_all_2016-05-10.vc700.gca transforms/talairach_with_skull.lta valid intensity range = [26, 116] 9808 zero brain voxels -124143 brainmask_orig_nu_PFH30.auto.mgz log_likelihood= -124143 mri_log_likelihood -orig T1.mgz brainmask_T1_PFH5.auto.mgz /usr/local/freesurfer/average/RB_all_2016-05-10.vc700.gca transforms/talairach_with_skull.lta valid intensity range = [26, 116] 10682 zero brain voxels -62437 brainmask_T1_PFH5.auto.mgz log_likelihood= -62437 mri_log_likelihood -orig T1.mgz brainmask_T1_PFH10.auto.mgz /usr/local/freesurfer/average/RB_all_2016-05-10.vc700.gca transforms/talairach_with_skull.lta valid intensity range = [26, 116] 10895 zero brain voxels -62465 brainmask_T1_PFH10.auto.mgz log_likelihood= -62465 mri_log_likelihood -orig T1.mgz brainmask_T1_PFH20.auto.mgz /usr/local/freesurfer/average/RB_all_2016-05-10.vc700.gca transforms/talairach_with_skull.lta valid intensity range = [26, 116] 9979 zero brain voxels -62424 brainmask_T1_PFH20.auto.mgz log_likelihood= -62424 mri_log_likelihood -orig T1.mgz brainmask_T1_PFH30.auto.mgz /usr/local/freesurfer/average/RB_all_2016-05-10.vc700.gca transforms/talairach_with_skull.lta valid intensity range = [26, 116] 9071 zero brain voxels -62887 brainmask_T1_PFH30.auto.mgz log_likelihood= -62887 Optimal input vol: orig, pre-flood height= 10, results in log_likelihood= -62278 cp brainmask.auto.mgz brainmask.mgz #------------------------------------- #@# EM Registration Mon Sep 11 10:15:22 CEST 2017 /home/gc/study/recon-all/400614bash/mri mri_em_register -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_em_register.dat -uns 3 -mask brainmask.mgz nu.mgz /usr/local/freesurfer/average/RB_all_2016-05-10.vc700.gca transforms/talairach.lta setting unknown_nbr_spacing = 3 using MR volume brainmask.mgz to mask input volume... == Number of threads available to mri_em_register for OpenMP = 1 == reading 1 input volumes... logging results to talairach.log reading '/usr/local/freesurfer/average/RB_all_2016-05-10.vc700.gca'... average std = 7.3 using min determinant for regularization = 5.3 0 singular and 841 ill-conditioned covariance matrices regularized reading 'nu.mgz'... freeing gibbs priors...done. accounting for voxel sizes in initial transform bounding unknown intensity as < 6.3 or > 503.7 total sample mean = 78.8 (1011 zeros) ************************************************ spacing=8, using 2830 sample points, tol=1.00e-05... ************************************************ register_mri: find_optimal_transform find_optimal_transform: nsamples 2830, passno 0, spacing 8 resetting wm mean[0]: 98 --> 107 resetting gm mean[0]: 61 --> 61 input volume #1 is the most T1-like using real data threshold=19.0 skull bounding box = (63, 43, 30) --> (191, 176, 199) using (106, 87, 115) as brain centroid... mean wm in atlas = 107, using box (90,71,94) --> (121, 103,135) to find MRI wm before smoothing, mri peak at 107 robust fit to distribution - 106 +- 3.8 after smoothing, mri peak at 106, scaling input intensities by 1.009 scaling channel 0 by 1.00943 initial log_p = -4.268 ************************************************ First Search limited to translation only. ************************************************ max log p = -4.167687 @ (-9.091, 9.091, -9.091) max log p = -3.922309 @ (13.636, 4.545, 4.545) max log p = -3.881292 @ (-6.818, 6.818, 2.273) max log p = -3.830825 @ (3.409, -5.682, -3.409) max log p = -3.830825 @ (0.000, 0.000, 0.000) max log p = -3.830825 @ (0.000, 0.000, 0.000) Found translation: (1.1, 14.8, -5.7): log p = -3.831 **************************************** Nine parameter search. iteration 0 nscales = 0 ... **************************************** Result so far: scale 1.000: max_log_p=-3.772, old_max_log_p =-3.831 (thresh=-3.8) 1.07500 0.00000 0.00000 -8.28371; 0.00000 1.07500 0.00000 6.93393; 0.00000 0.00000 0.92500 2.65264; 0.00000 0.00000 0.00000 1.00000; **************************************** Nine parameter search. iteration 1 nscales = 0 ... **************************************** Result so far: scale 1.000: max_log_p=-3.772, old_max_log_p =-3.772 (thresh=-3.8) 1.07500 0.00000 0.00000 -8.28371; 0.00000 1.07500 0.00000 6.93393; 0.00000 0.00000 0.92500 2.65264; 0.00000 0.00000 0.00000 1.00000; reducing scale to 0.2500 **************************************** Nine parameter search. iteration 2 nscales = 1 ... **************************************** Result so far: scale 0.250: max_log_p=-3.664, old_max_log_p =-3.772 (thresh=-3.8) 1.05249 -0.06492 -0.01607 0.97403; 0.06293 1.05211 0.18193 -18.56639; -0.00520 -0.21881 0.95892 26.20923; 0.00000 0.00000 0.00000 1.00000; **************************************** Nine parameter search. iteration 3 nscales = 1 ... **************************************** Result so far: scale 0.250: max_log_p=-3.664, old_max_log_p =-3.664 (thresh=-3.7) 1.05249 -0.06492 -0.01607 0.97403; 0.06293 1.05211 0.18193 -18.56639; -0.00520 -0.21881 0.95892 26.20923; 0.00000 0.00000 0.00000 1.00000; reducing scale to 0.0625 **************************************** Nine parameter search. iteration 4 nscales = 2 ... **************************************** Result so far: scale 0.062: max_log_p=-3.644, old_max_log_p =-3.664 (thresh=-3.7) 1.05494 -0.03928 -0.01083 -2.12920; 0.03688 1.04430 0.21380 -18.77170; -0.00731 -0.25457 0.95569 29.61992; 0.00000 0.00000 0.00000 1.00000; **************************************** Nine parameter search. iteration 5 nscales = 2 ... **************************************** Result so far: scale 0.062: max_log_p=-3.637, old_max_log_p =-3.644 (thresh=-3.6) 1.05494 -0.03928 -0.01083 -2.12920; 0.03688 1.04430 0.21380 -18.77170; -0.00733 -0.25546 0.95906 29.35313; 0.00000 0.00000 0.00000 1.00000; **************************************** Nine parameter search. iteration 6 nscales = 2 ... **************************************** Result so far: scale 0.062: max_log_p=-3.637, old_max_log_p =-3.637 (thresh=-3.6) 1.05494 -0.03928 -0.01083 -2.12920; 0.03688 1.04430 0.21380 -18.77170; -0.00733 -0.25546 0.95906 29.35313; 0.00000 0.00000 0.00000 1.00000; min search scale 0.025000 reached *********************************************** Computing MAP estimate using 2830 samples... *********************************************** dt = 5.00e-06, momentum=0.80, tol=1.00e-05 l_intensity = 1.0000 Aligning input volume to GCA... Transform matrix 1.05494 -0.03928 -0.01083 -2.12920; 0.03688 1.04430 0.21380 -18.77170; -0.00733 -0.25546 0.95906 29.35313; 0.00000 0.00000 0.00000 1.00000; nsamples 2830 Quasinewton: input matrix 1.05494 -0.03928 -0.01083 -2.12920; 0.03688 1.04430 0.21380 -18.77170; -0.00733 -0.25546 0.95906 29.35313; 0.00000 0.00000 0.00000 1.00000; outof QuasiNewtonEMA: 009: -log(p) = -0.0 tol 0.000010 Resulting transform: 1.05494 -0.03928 -0.01083 -2.12920; 0.03688 1.04430 0.21380 -18.77170; -0.00733 -0.25546 0.95906 29.35313; 0.00000 0.00000 0.00000 1.00000; pass 1, spacing 8: log(p) = -3.637 (old=-4.268) transform before final EM align: 1.05494 -0.03928 -0.01083 -2.12920; 0.03688 1.04430 0.21380 -18.77170; -0.00733 -0.25546 0.95906 29.35313; 0.00000 0.00000 0.00000 1.00000; ************************************************** EM alignment process ... Computing final MAP estimate using 315557 samples. ************************************************** dt = 5.00e-06, momentum=0.80, tol=1.00e-07 l_intensity = 1.0000 Aligning input volume to GCA... Transform matrix 1.05494 -0.03928 -0.01083 -2.12920; 0.03688 1.04430 0.21380 -18.77170; -0.00733 -0.25546 0.95906 29.35313; 0.00000 0.00000 0.00000 1.00000; nsamples 315557 Quasinewton: input matrix 1.05494 -0.03928 -0.01083 -2.12920; 0.03688 1.04430 0.21380 -18.77170; -0.00733 -0.25546 0.95906 29.35313; 0.00000 0.00000 0.00000 1.00000; outof QuasiNewtonEMA: 011: -log(p) = 4.1 tol 0.000000 final transform: 1.05494 -0.03928 -0.01083 -2.12920; 0.03688 1.04430 0.21380 -18.77170; -0.00733 -0.25546 0.95906 29.35313; 0.00000 0.00000 0.00000 1.00000; writing output transformation to transforms/talairach.lta... mri_em_register utimesec 998.789160 mri_em_register stimesec 0.621905 mri_em_register ru_maxrss 598996 mri_em_register ru_ixrss 0 mri_em_register ru_idrss 0 mri_em_register ru_isrss 0 mri_em_register ru_minflt 158524 mri_em_register ru_majflt 43 mri_em_register ru_nswap 0 mri_em_register ru_inblock 8488 mri_em_register ru_oublock 16 mri_em_register ru_msgsnd 0 mri_em_register ru_msgrcv 0 mri_em_register ru_nsignals 0 mri_em_register ru_nvcsw 71 mri_em_register ru_nivcsw 101496 registration took 16 minutes and 42 seconds. #-------------------------------------- #@# CA Normalize Mon Sep 11 10:32:05 CEST 2017 /home/gc/study/recon-all/400614bash/mri mri_ca_normalize -c ctrl_pts.mgz -mask brainmask.mgz nu.mgz /usr/local/freesurfer/average/RB_all_2016-05-10.vc700.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_2016-05-10.vc700.gca'... reading transform from 'transforms/talairach.lta'... reading input volume from nu.mgz... resetting wm mean[0]: 98 --> 107 resetting gm mean[0]: 61 --> 61 input volume #1 is the most T1-like using real data threshold=18.0 skull bounding box = (63, 43, 30) --> (191, 176, 199) using (106, 87, 115) as brain centroid... mean wm in atlas = 107, using box (90,71,94) --> (121, 103,135) to find MRI wm before smoothing, mri peak at 107 robust fit to distribution - 106 +- 3.8 after smoothing, mri peak at 106, scaling input intensities by 1.009 scaling channel 0 by 1.00943 using 246344 sample points... INFO: compute sample coordinates transform 1.05494 -0.03928 -0.01083 -2.12920; 0.03688 1.04430 0.21380 -18.77170; -0.00733 -0.25546 0.95906 29.35313; 0.00000 0.00000 0.00000 1.00000; INFO: transform used finding control points in Left_Cerebral_White_Matter.... found 39915 control points for structure... bounding box (126, 43, 31) --> (190, 150, 199) Left_Cerebral_White_Matter: limiting intensities to 98.0 --> 132.0 4 of 4957 (0.1%) samples deleted finding control points in Right_Cerebral_White_Matter.... found 39557 control points for structure... bounding box (65, 45, 30) --> (128, 151, 200) Right_Cerebral_White_Matter: limiting intensities to 96.0 --> 132.0 8 of 5650 (0.1%) samples deleted finding control points in Left_Cerebellum_White_Matter.... found 3059 control points for structure... bounding box (129, 129, 61) --> (176, 167, 116) Left_Cerebellum_White_Matter: limiting intensities to 102.0 --> 132.0 0 of 96 (0.0%) samples deleted finding control points in Right_Cerebellum_White_Matter.... found 2705 control points for structure... bounding box (87, 129, 59) --> (128, 168, 117) Right_Cerebellum_White_Matter: limiting intensities to 115.0 --> 132.0 25 of 68 (36.8%) samples deleted finding control points in Brain_Stem.... found 3518 control points for structure... bounding box (112, 116, 98) --> (145, 182, 128) Brain_Stem: limiting intensities to 96.0 --> 132.0 0 of 250 (0.0%) samples deleted using 11021 total control points for intensity normalization... bias field = 0.968 +- 0.062 158 of 10984 control points discarded finding control points in Left_Cerebral_White_Matter.... found 39915 control points for structure... bounding box (126, 43, 31) --> (190, 150, 199) Left_Cerebral_White_Matter: limiting intensities to 90.0 --> 132.0 4 of 5510 (0.1%) samples deleted finding control points in Right_Cerebral_White_Matter.... found 39557 control points for structure... bounding box (65, 45, 30) --> (128, 151, 200) Right_Cerebral_White_Matter: limiting intensities to 88.0 --> 132.0 14 of 5932 (0.2%) samples deleted finding control points in Left_Cerebellum_White_Matter.... found 3059 control points for structure... bounding box (129, 129, 61) --> (176, 167, 116) Left_Cerebellum_White_Matter: limiting intensities to 88.0 --> 132.0 17 of 147 (11.6%) samples deleted finding control points in Right_Cerebellum_White_Matter.... found 2705 control points for structure... bounding box (87, 129, 59) --> (128, 168, 117) Right_Cerebellum_White_Matter: limiting intensities to 88.0 --> 132.0 9 of 143 (6.3%) samples deleted finding control points in Brain_Stem.... found 3518 control points for structure... bounding box (112, 116, 98) --> (145, 182, 128) Brain_Stem: limiting intensities to 88.0 --> 107.0 7 of 324 (2.2%) samples deleted using 12056 total control points for intensity normalization... bias field = 1.052 +- 0.059 90 of 11922 control points discarded finding control points in Left_Cerebral_White_Matter.... found 39915 control points for structure... bounding box (126, 43, 31) --> (190, 150, 199) Left_Cerebral_White_Matter: limiting intensities to 90.0 --> 132.0 21 of 5480 (0.4%) samples deleted finding control points in Right_Cerebral_White_Matter.... found 39557 control points for structure... bounding box (65, 45, 30) --> (128, 151, 200) Right_Cerebral_White_Matter: limiting intensities to 88.0 --> 132.0 27 of 5987 (0.5%) samples deleted finding control points in Left_Cerebellum_White_Matter.... found 3059 control points for structure... bounding box (129, 129, 61) --> (176, 167, 116) Left_Cerebellum_White_Matter: limiting intensities to 88.0 --> 132.0 98 of 213 (46.0%) samples deleted finding control points in Right_Cerebellum_White_Matter.... found 2705 control points for structure... bounding box (87, 129, 59) --> (128, 168, 117) Right_Cerebellum_White_Matter: limiting intensities to 88.0 --> 132.0 28 of 170 (16.5%) samples deleted finding control points in Brain_Stem.... found 3518 control points for structure... bounding box (112, 116, 98) --> (145, 182, 128) Brain_Stem: limiting intensities to 88.0 --> 132.0 33 of 336 (9.8%) samples deleted using 12186 total control points for intensity normalization... bias field = 1.048 +- 0.051 72 of 11809 control points discarded writing normalized volume to norm.mgz... writing control points to ctrl_pts.mgz freeing GCA...done. normalization took 1 minutes and 46 seconds. #-------------------------------------- #@# CA Reg Mon Sep 11 10:33:51 CEST 2017 /home/gc/study/recon-all/400614bash/mri mri_ca_register -rusage /home/gc/study/recon-all/400614bash/touch/rusage.mri_ca_register.dat -nobigventricles -T transforms/talairach.lta -align-after -mask brainmask.mgz norm.mgz /usr/local/freesurfer/average/RB_all_2016-05-10.vc700.gca transforms/talairach.m3z not handling expanded ventricles... using previously computed transform transforms/talairach.lta renormalizing sequences with structure alignment, equivalent to: -renormalize -regularize_mean 0.500 -regularize 0.500 using MR volume brainmask.mgz to mask input volume... == Number of threads available to mri_ca_register for OpenMP = 1 == reading 1 input volumes... logging results to talairach.log reading input volume 'norm.mgz'... reading GCA '/usr/local/freesurfer/average/RB_all_2016-05-10.vc700.gca'... label assignment complete, 0 changed (0.00%) det(m_affine) = 1.12 (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 ************************ enabling zero nodes setting smoothness coefficient to 0.039 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.884, neg=0, invalid=762 0001: dt=295.936000, rms=0.787 (11.061%), neg=0, invalid=762 0002: dt=154.020534, rms=0.765 (2.708%), neg=0, invalid=762 0003: dt=369.920000, rms=0.751 (1.903%), neg=0, invalid=762 0004: dt=129.472000, rms=0.745 (0.739%), neg=0, invalid=762 0005: dt=517.888000, rms=0.738 (0.959%), neg=0, invalid=762 0006: dt=129.472000, rms=0.736 (0.328%), neg=0, invalid=762 0007: dt=517.888000, rms=0.732 (0.492%), neg=0, invalid=762 0008: dt=110.976000, rms=0.730 (0.299%), neg=0, invalid=762 0009: dt=1183.744000, rms=0.726 (0.528%), neg=0, invalid=762 0010: dt=92.480000, rms=0.724 (0.255%), neg=0, invalid=762 0011: dt=887.808000, rms=0.722 (0.296%), neg=0, invalid=762 0012: dt=129.472000, rms=0.720 (0.214%), neg=0, invalid=762 0013: dt=129.472000, rms=0.720 (0.007%), neg=0, invalid=762 0014: dt=129.472000, rms=0.720 (0.035%), neg=0, invalid=762 0015: dt=129.472000, rms=0.719 (0.120%), neg=0, invalid=762 0016: dt=129.472000, rms=0.718 (0.168%), neg=0, invalid=762 0017: dt=129.472000, rms=0.717 (0.181%), neg=0, invalid=762 0018: dt=129.472000, rms=0.716 (0.169%), neg=0, invalid=762 0019: dt=129.472000, rms=0.714 (0.158%), neg=0, invalid=762 0020: dt=129.472000, rms=0.713 (0.162%), neg=0, invalid=762 0021: dt=129.472000, rms=0.712 (0.150%), neg=0, invalid=762 0022: dt=129.472000, rms=0.711 (0.121%), neg=0, invalid=762 0023: dt=129.472000, rms=0.711 (0.114%), neg=0, invalid=762 0024: dt=1479.680000, rms=0.708 (0.366%), neg=0, invalid=762 0025: dt=32.368000, rms=0.708 (0.043%), neg=0, invalid=762 0026: dt=32.368000, rms=0.708 (-0.007%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.708, neg=0, invalid=762 0027: dt=129.472000, rms=0.705 (0.387%), neg=0, invalid=762 0028: dt=517.888000, rms=0.703 (0.319%), neg=0, invalid=762 0029: dt=129.472000, rms=0.703 (0.047%), neg=0, invalid=762 0030: dt=129.472000, rms=0.703 (0.036%), neg=0, invalid=762 0031: dt=129.472000, rms=0.702 (0.053%), neg=0, invalid=762 0032: dt=129.472000, rms=0.702 (0.071%), neg=0, invalid=762 0033: dt=129.472000, rms=0.701 (0.093%), neg=0, invalid=762 0034: dt=129.472000, rms=0.700 (0.100%), neg=0, invalid=762 0035: dt=129.472000, rms=0.700 (0.113%), neg=0, invalid=762 0036: dt=129.472000, rms=0.699 (0.101%), neg=0, invalid=762 0037: dt=129.472000, rms=0.698 (0.098%), neg=0, invalid=762 0038: dt=517.888000, rms=0.698 (0.028%), neg=0, invalid=762 setting smoothness coefficient to 0.154 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.705, neg=0, invalid=762 0039: dt=36.288000, rms=0.703 (0.257%), neg=0, invalid=762 0040: dt=114.346667, rms=0.701 (0.400%), neg=0, invalid=762 0041: dt=286.034274, rms=0.683 (2.482%), neg=0, invalid=762 0042: dt=22.496241, rms=0.681 (0.319%), neg=0, invalid=762 0043: dt=7.776000, rms=0.681 (0.014%), neg=0, invalid=762 0044: dt=7.776000, rms=0.681 (0.005%), neg=0, invalid=762 0045: dt=7.776000, rms=0.681 (-0.026%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.681, neg=0, invalid=762 0046: dt=217.600000, rms=0.675 (0.882%), neg=0, invalid=762 0047: dt=60.279070, rms=0.674 (0.286%), neg=0, invalid=762 0048: dt=97.054945, rms=0.672 (0.279%), neg=0, invalid=762 0049: dt=36.288000, rms=0.671 (0.136%), neg=0, invalid=762 0050: dt=36.288000, rms=0.670 (0.075%), neg=0, invalid=762 0051: dt=36.288000, rms=0.669 (0.131%), neg=0, invalid=762 0052: dt=36.288000, rms=0.668 (0.185%), neg=0, invalid=762 0053: dt=36.288000, rms=0.667 (0.237%), neg=0, invalid=762 0054: dt=36.288000, rms=0.665 (0.269%), neg=0, invalid=762 0055: dt=36.288000, rms=0.663 (0.278%), neg=0, invalid=762 0056: dt=36.288000, rms=0.661 (0.281%), neg=0, invalid=762 0057: dt=36.288000, rms=0.659 (0.265%), neg=0, invalid=762 0058: dt=36.288000, rms=0.658 (0.252%), neg=0, invalid=762 0059: dt=36.288000, rms=0.656 (0.245%), neg=0, invalid=762 0060: dt=36.288000, rms=0.654 (0.238%), neg=0, invalid=762 0061: dt=36.288000, rms=0.653 (0.243%), neg=0, invalid=762 0062: dt=36.288000, rms=0.651 (0.231%), neg=0, invalid=762 0063: dt=36.288000, rms=0.650 (0.219%), neg=0, invalid=762 0064: dt=36.288000, rms=0.649 (0.204%), neg=0, invalid=762 0065: dt=36.288000, rms=0.647 (0.189%), neg=0, invalid=762 0066: dt=36.288000, rms=0.646 (0.170%), neg=0, invalid=762 0067: dt=36.288000, rms=0.645 (0.153%), neg=0, invalid=762 0068: dt=36.288000, rms=0.644 (0.139%), neg=0, invalid=762 0069: dt=36.288000, rms=0.643 (0.147%), neg=0, invalid=762 0070: dt=36.288000, rms=0.643 (0.135%), neg=0, invalid=762 0071: dt=36.288000, rms=0.642 (0.123%), neg=0, invalid=762 0072: dt=36.288000, rms=0.641 (0.112%), neg=0, invalid=762 0073: dt=36.288000, rms=0.641 (0.003%), neg=0, invalid=762 0074: dt=36.288000, rms=0.641 (0.011%), neg=0, invalid=762 0075: dt=36.288000, rms=0.641 (0.014%), neg=0, invalid=762 0076: dt=36.288000, rms=0.641 (0.016%), neg=0, invalid=762 0077: dt=36.288000, rms=0.641 (0.022%), neg=0, invalid=762 0078: dt=36.288000, rms=0.640 (0.023%), neg=0, invalid=762 0079: dt=36.288000, rms=0.640 (0.025%), neg=0, invalid=762 0080: dt=36.288000, rms=0.640 (0.027%), neg=0, invalid=762 0081: dt=36.288000, rms=0.640 (0.030%), neg=0, invalid=762 0082: dt=36.288000, rms=0.640 (0.037%), neg=0, invalid=762 0083: dt=36.288000, rms=0.639 (0.037%), neg=0, invalid=762 0084: dt=36.288000, rms=0.639 (0.035%), neg=0, invalid=762 0085: dt=36.288000, rms=0.639 (0.041%), neg=0, invalid=762 0086: dt=36.288000, rms=0.639 (0.042%), neg=0, invalid=762 0087: dt=36.288000, rms=0.638 (0.048%), neg=0, invalid=762 0088: dt=36.288000, rms=0.638 (0.041%), neg=0, invalid=762 setting smoothness coefficient to 0.588 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.666, neg=0, invalid=762 0089: dt=2.800000, rms=0.665 (0.113%), neg=0, invalid=762 0090: dt=2.800000, rms=0.665 (0.011%), neg=0, invalid=762 0091: dt=2.800000, rms=0.665 (0.002%), neg=0, invalid=762 0092: dt=2.800000, rms=0.665 (-0.023%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.666, neg=0, invalid=762 0093: dt=0.500000, rms=0.665 (0.087%), neg=0, invalid=762 0094: dt=0.100000, rms=0.665 (-0.000%), neg=0, invalid=762 setting smoothness coefficient to 2.000 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.741, neg=0, invalid=762 0095: dt=6.344322, rms=0.720 (2.915%), neg=0, invalid=762 0096: dt=7.085714, rms=0.717 (0.442%), neg=0, invalid=762 0097: dt=3.818182, rms=0.716 (0.038%), neg=0, invalid=762 0098: dt=3.818182, rms=0.716 (0.025%), neg=0, invalid=762 0099: dt=3.818182, rms=0.716 (-0.022%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.717, neg=0, invalid=762 0100: dt=0.000000, rms=0.716 (0.072%), neg=0, invalid=762 0101: dt=0.000000, rms=0.716 (0.000%), neg=0, invalid=762 setting smoothness coefficient to 5.000 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.774, neg=0, invalid=762 0102: dt=0.000000, rms=0.774 (0.061%), neg=0, invalid=762 0103: dt=0.000000, rms=0.774 (0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.774, neg=0, invalid=762 0104: dt=0.064000, rms=0.774 (0.063%), neg=0, invalid=762 0105: dt=0.028000, rms=0.774 (0.000%), neg=0, invalid=762 0106: dt=0.028000, rms=0.774 (0.001%), neg=0, invalid=762 0107: dt=0.028000, rms=0.774 (-0.001%), neg=0, invalid=762 resetting metric properties... setting smoothness coefficient to 10.000 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.678, neg=0, invalid=762 0108: dt=0.724359, rms=0.663 (2.126%), neg=0, invalid=762 0109: dt=0.064000, rms=0.663 (0.079%), neg=0, invalid=762 0110: dt=0.064000, rms=0.663 (-0.053%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.663, neg=0, invalid=762 0111: dt=0.028000, rms=0.662 (0.098%), neg=0, invalid=762 0112: dt=0.001500, rms=0.663 (-0.001%), neg=0, invalid=762 renormalizing by structure alignment.... renormalizing input #0 gca peak = 0.10027 (20) mri peak = 0.07080 (32) Left_Lateral_Ventricle (4): linear fit = 1.91 x + 0.0 (1315 voxels, overlap=0.107) Left_Lateral_Ventricle (4): linear fit = 1.50 x + 0.0 (1315 voxels, peak = 38), gca=30.0 gca peak = 0.15565 (16) mri peak = 0.10377 (33) Right_Lateral_Ventricle (43): linear fit = 2.13 x + 0.0 (1094 voxels, overlap=0.038) Right_Lateral_Ventricle (43): linear fit = 1.50 x + 0.0 (1094 voxels, peak = 34), gca=24.0 gca peak = 0.26829 (96) mri peak = 0.10192 (99) Right_Pallidum (52): linear fit = 1.02 x + 0.0 (1039 voxels, overlap=1.000) Right_Pallidum (52): linear fit = 1.02 x + 0.0 (1039 voxels, peak = 98), gca=98.4 gca peak = 0.20183 (93) mri peak = 0.08247 (99) Left_Pallidum (13): linear fit = 1.03 x + 0.0 (965 voxels, overlap=1.009) Left_Pallidum (13): linear fit = 1.03 x + 0.0 (965 voxels, peak = 96), gca=96.3 gca peak = 0.21683 (55) mri peak = 0.12251 (74) Right_Hippocampus (53): linear fit = 1.29 x + 0.0 (1252 voxels, overlap=0.011) Right_Hippocampus (53): linear fit = 1.29 x + 0.0 (1252 voxels, peak = 71), gca=71.2 gca peak = 0.30730 (58) mri peak = 0.08144 (72) Left_Hippocampus (17): linear fit = 1.25 x + 0.0 (1287 voxels, overlap=0.024) Left_Hippocampus (17): linear fit = 1.25 x + 0.0 (1287 voxels, peak = 73), gca=72.8 gca peak = 0.11430 (101) mri peak = 0.12239 (102) Right_Cerebral_White_Matter (41): linear fit = 1.00 x + 0.0 (77851 voxels, overlap=0.806) Right_Cerebral_White_Matter (41): linear fit = 1.00 x + 0.0 (77851 voxels, peak = 102), gca=101.5 gca peak = 0.12076 (102) mri peak = 0.12571 (103) Left_Cerebral_White_Matter (2): linear fit = 1.01 x + 0.0 (77836 voxels, overlap=0.719) Left_Cerebral_White_Matter (2): linear fit = 1.01 x + 0.0 (77836 voxels, peak = 104), gca=103.5 gca peak = 0.14995 (59) mri peak = 0.03622 (82) Left_Cerebral_Cortex (3): linear fit = 1.35 x + 0.0 (33103 voxels, overlap=0.000) Left_Cerebral_Cortex (3): linear fit = 1.35 x + 0.0 (33103 voxels, peak = 79), gca=79.4 gca peak = 0.15082 (58) mri peak = 0.03765 (81) Right_Cerebral_Cortex (42): linear fit = 1.38 x + 0.0 (34685 voxels, overlap=0.000) Right_Cerebral_Cortex (42): linear fit = 1.38 x + 0.0 (34685 voxels, peak = 80), gca=79.8 gca peak = 0.14161 (67) mri peak = 0.11886 (83) Right_Caudate (50): linear fit = 1.23 x + 0.0 (896 voxels, overlap=0.009) Right_Caudate (50): linear fit = 1.23 x + 0.0 (896 voxels, peak = 82), gca=82.1 gca peak = 0.15243 (71) mri peak = 0.11194 (88) Left_Caudate (11): linear fit = 1.21 x + 0.0 (1194 voxels, overlap=0.020) Left_Caudate (11): linear fit = 1.21 x + 0.0 (1194 voxels, peak = 86), gca=85.6 gca peak = 0.13336 (57) mri peak = 0.04889 (78) Left_Cerebellum_Cortex (8): linear fit = 1.40 x + 0.0 (25281 voxels, overlap=0.001) Left_Cerebellum_Cortex (8): linear fit = 1.40 x + 0.0 (25281 voxels, peak = 80), gca=80.1 gca peak = 0.13252 (56) mri peak = 0.05424 (78) Right_Cerebellum_Cortex (47): linear fit = 1.38 x + 0.0 (25646 voxels, overlap=0.001) Right_Cerebellum_Cortex (47): linear fit = 1.38 x + 0.0 (25646 voxels, peak = 77), gca=77.0 gca peak = 0.18181 (84) mri peak = 0.04148 (89) Left_Cerebellum_White_Matter (7): linear fit = 1.05 x + 0.0 (9691 voxels, overlap=0.924) Left_Cerebellum_White_Matter (7): linear fit = 1.05 x + 0.0 (9691 voxels, peak = 89), gca=88.6 gca peak = 0.20573 (83) mri peak = 0.06546 (90) Right_Cerebellum_White_Matter (46): linear fit = 1.09 x + 0.0 (8173 voxels, overlap=0.773) Right_Cerebellum_White_Matter (46): linear fit = 1.09 x + 0.0 (8173 voxels, peak = 90), gca=90.1 gca peak = 0.21969 (57) mri peak = 0.10843 (79) Left_Amygdala (18): linear fit = 1.38 x + 0.0 (539 voxels, overlap=0.061) Left_Amygdala (18): linear fit = 1.38 x + 0.0 (539 voxels, peak = 78), gca=78.4 gca peak = 0.39313 (56) mri peak = 0.09206 (78) Right_Amygdala (54): linear fit = 1.38 x + 0.0 (601 voxels, overlap=0.049) Right_Amygdala (54): linear fit = 1.38 x + 0.0 (601 voxels, peak = 78), gca=77.6 gca peak = 0.14181 (85) mri peak = 0.09322 (95) Left_Thalamus_Proper (10): linear fit = 1.11 x + 0.0 (6193 voxels, overlap=0.339) Left_Thalamus_Proper (10): linear fit = 1.11 x + 0.0 (6193 voxels, peak = 94), gca=93.9 gca peak = 0.11978 (83) mri peak = 0.08378 (95) Right_Thalamus_Proper (49): linear fit = 1.13 x + 0.0 (5102 voxels, overlap=0.184) Right_Thalamus_Proper (49): linear fit = 1.13 x + 0.0 (5102 voxels, peak = 94), gca=94.2 gca peak = 0.13399 (79) mri peak = 0.10972 (88) Left_Putamen (12): linear fit = 1.12 x + 0.0 (2707 voxels, overlap=0.157) Left_Putamen (12): linear fit = 1.12 x + 0.0 (2707 voxels, peak = 88), gca=88.1 gca peak = 0.14159 (79) mri peak = 0.11681 (88) Right_Putamen (51): linear fit = 1.14 x + 0.0 (2806 voxels, overlap=0.016) Right_Putamen (51): linear fit = 1.14 x + 0.0 (2806 voxels, peak = 90), gca=90.5 gca peak = 0.10025 (80) mri peak = 0.08520 (92) Brain_Stem (16): linear fit = 1.15 x + 0.0 (11912 voxels, overlap=0.029) Brain_Stem (16): linear fit = 1.15 x + 0.0 (11912 voxels, peak = 92), gca=92.4 gca peak = 0.13281 (86) mri peak = 0.07423 (97) Right_VentralDC (60): linear fit = 1.14 x + 0.0 (1464 voxels, overlap=0.117) Right_VentralDC (60): linear fit = 1.14 x + 0.0 (1464 voxels, peak = 98), gca=98.5 gca peak = 0.12801 (89) mri peak = 0.08611 (98) Left_VentralDC (28): linear fit = 1.10 x + 0.0 (1571 voxels, overlap=0.392) Left_VentralDC (28): linear fit = 1.10 x + 0.0 (1571 voxels, peak = 97), gca=97.5 gca peak = 0.20494 (23) mri peak = 0.36364 (32) gca peak = 0.15061 (21) mri peak = 0.33341 (34) Fourth_Ventricle (15): linear fit = 1.55 x + 0.0 (817 voxels, overlap=0.074) Fourth_Ventricle (15): linear fit = 1.55 x + 0.0 (817 voxels, peak = 33), gca=32.7 gca peak Unknown = 0.94835 ( 0) gca peak Left_Inf_Lat_Vent = 0.18056 (32) gca peak Left_Thalamus = 0.64095 (94) gca peak Third_Ventricle = 0.20494 (23) gca peak Fourth_Ventricle = 0.15061 (21) gca peak CSF = 0.20999 (34) gca peak Left_Accumbens_area = 0.39030 (62) gca peak Left_undetermined = 0.95280 (25) gca peak Left_vessel = 0.67734 (53) gca peak Left_choroid_plexus = 0.09433 (44) gca peak Right_Inf_Lat_Vent = 0.23544 (26) gca peak Right_Accumbens_area = 0.30312 (64) gca peak Right_vessel = 0.46315 (51) gca peak Right_choroid_plexus = 0.14086 (44) gca peak Fifth_Ventricle = 0.51669 (36) gca peak WM_hypointensities = 0.09722 (76) gca peak non_WM_hypointensities = 0.11899 (47) gca peak Optic_Chiasm = 0.39033 (72) label assignment complete, 0 changed (0.00%) not using caudate to estimate GM means estimating mean gm scale to be 1.34 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 ************************ enabling zero nodes setting smoothness coefficient to 0.008 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.656, neg=0, invalid=762 0113: dt=107.429365, rms=0.623 (4.993%), neg=0, invalid=762 0114: dt=295.936000, rms=0.614 (1.430%), neg=0, invalid=762 0115: dt=143.170370, rms=0.611 (0.519%), neg=0, invalid=762 0116: dt=295.936000, rms=0.609 (0.407%), neg=0, invalid=762 0117: dt=92.480000, rms=0.608 (0.178%), neg=0, invalid=762 0118: dt=517.888000, rms=0.606 (0.189%), neg=0, invalid=762 0119: dt=129.472000, rms=0.605 (0.206%), neg=0, invalid=762 0120: dt=92.480000, rms=0.605 (0.042%), neg=0, invalid=762 0121: dt=92.480000, rms=0.605 (0.041%), neg=0, invalid=762 0122: dt=92.480000, rms=0.604 (0.072%), neg=0, invalid=762 0123: dt=92.480000, rms=0.604 (0.092%), neg=0, invalid=762 0124: dt=92.480000, rms=0.603 (0.108%), neg=0, invalid=762 0125: dt=92.480000, rms=0.602 (0.116%), neg=0, invalid=762 0126: dt=92.480000, rms=0.602 (0.115%), neg=0, invalid=762 0127: dt=92.480000, rms=0.601 (0.105%), neg=0, invalid=762 0128: dt=92.480000, rms=0.600 (0.099%), neg=0, invalid=762 0129: dt=92.480000, rms=0.600 (0.092%), neg=0, invalid=762 0130: dt=92.480000, rms=0.599 (0.091%), neg=0, invalid=762 0131: dt=92.480000, rms=0.599 (0.086%), neg=0, invalid=762 0132: dt=92.480000, rms=0.598 (0.081%), neg=0, invalid=762 0133: dt=92.480000, rms=0.598 (0.074%), neg=0, invalid=762 0134: dt=92.480000, rms=0.597 (0.076%), neg=0, invalid=762 0135: dt=92.480000, rms=0.597 (0.078%), neg=0, invalid=762 0136: dt=92.480000, rms=0.596 (0.083%), neg=0, invalid=762 0137: dt=92.480000, rms=0.596 (0.082%), neg=0, invalid=762 0138: dt=92.480000, rms=0.595 (0.073%), neg=0, invalid=762 0139: dt=92.480000, rms=0.595 (0.068%), neg=0, invalid=762 0140: dt=92.480000, rms=0.595 (0.069%), neg=0, invalid=762 0141: dt=92.480000, rms=0.594 (0.067%), neg=0, invalid=762 0142: dt=92.480000, rms=0.594 (0.068%), neg=0, invalid=762 0143: dt=92.480000, rms=0.593 (0.072%), neg=0, invalid=762 0144: dt=92.480000, rms=0.593 (0.067%), neg=0, invalid=762 0145: dt=92.480000, rms=0.593 (0.067%), neg=0, invalid=762 0146: dt=92.480000, rms=0.592 (0.058%), neg=0, invalid=762 0147: dt=92.480000, rms=0.592 (0.045%), neg=0, invalid=762 0148: dt=92.480000, rms=0.592 (0.043%), neg=0, invalid=762 0149: dt=92.480000, rms=0.592 (0.043%), neg=0, invalid=762 0150: dt=92.480000, rms=0.591 (0.048%), neg=0, invalid=762 0151: dt=92.480000, rms=0.591 (0.044%), neg=0, invalid=762 0152: dt=92.480000, rms=0.591 (0.041%), neg=0, invalid=762 0153: dt=92.480000, rms=0.591 (0.036%), neg=0, invalid=762 0154: dt=92.480000, rms=0.590 (0.028%), neg=0, invalid=762 0155: dt=92.480000, rms=0.590 (0.022%), neg=0, invalid=762 0156: dt=92.480000, rms=0.590 (0.026%), neg=0, invalid=762 0157: dt=92.480000, rms=0.590 (0.027%), neg=0, invalid=762 0158: dt=92.480000, rms=0.590 (0.030%), neg=0, invalid=762 0159: dt=92.480000, rms=0.590 (0.030%), neg=0, invalid=762 0160: dt=92.480000, rms=0.589 (0.026%), neg=0, invalid=762 0161: dt=92.480000, rms=0.589 (0.024%), neg=0, invalid=762 0162: dt=92.480000, rms=0.589 (0.025%), neg=0, invalid=762 0163: dt=92.480000, rms=0.589 (0.025%), neg=0, invalid=762 0164: dt=92.480000, rms=0.589 (0.027%), neg=0, invalid=762 0165: dt=92.480000, rms=0.589 (0.022%), neg=0, invalid=762 0166: dt=92.480000, rms=0.589 (0.026%), neg=0, invalid=762 0167: dt=92.480000, rms=0.588 (0.024%), neg=0, invalid=762 0168: dt=92.480000, rms=0.588 (0.020%), neg=0, invalid=762 0169: dt=517.888000, rms=0.588 (0.006%), neg=0, invalid=762 0170: dt=517.888000, rms=0.588 (-0.018%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.588, neg=0, invalid=762 0171: dt=221.952000, rms=0.587 (0.216%), neg=0, invalid=762 0172: dt=129.472000, rms=0.587 (0.053%), neg=0, invalid=762 0173: dt=887.808000, rms=0.586 (0.129%), neg=0, invalid=762 0174: dt=129.472000, rms=0.586 (0.046%), neg=0, invalid=762 0175: dt=129.472000, rms=0.586 (0.019%), neg=0, invalid=762 0176: dt=129.472000, rms=0.586 (0.016%), neg=0, invalid=762 0177: dt=129.472000, rms=0.585 (0.026%), neg=0, invalid=762 0178: dt=129.472000, rms=0.585 (0.024%), neg=0, invalid=762 0179: dt=129.472000, rms=0.585 (0.034%), neg=0, invalid=762 0180: dt=129.472000, rms=0.585 (0.038%), neg=0, invalid=762 0181: dt=129.472000, rms=0.585 (0.038%), neg=0, invalid=762 0182: dt=129.472000, rms=0.584 (0.036%), neg=0, invalid=762 0183: dt=129.472000, rms=0.584 (0.034%), neg=0, invalid=762 0184: dt=129.472000, rms=0.584 (0.040%), neg=0, invalid=762 0185: dt=129.472000, rms=0.584 (0.030%), neg=0, invalid=762 0186: dt=129.472000, rms=0.584 (0.031%), neg=0, invalid=762 0187: dt=129.472000, rms=0.583 (0.030%), neg=0, invalid=762 0188: dt=129.472000, rms=0.583 (0.026%), neg=0, invalid=762 0189: dt=129.472000, rms=0.583 (0.027%), neg=0, invalid=762 0190: dt=129.472000, rms=0.583 (0.030%), neg=0, invalid=762 0191: dt=129.472000, rms=0.583 (0.023%), neg=0, invalid=762 0192: dt=129.472000, rms=0.583 (0.022%), neg=0, invalid=762 0193: dt=887.808000, rms=0.583 (0.022%), neg=0, invalid=762 0194: dt=887.808000, rms=0.583 (-0.469%), neg=0, invalid=762 setting smoothness coefficient to 0.031 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.584, neg=0, invalid=762 0195: dt=65.049180, rms=0.583 (0.182%), neg=0, invalid=762 0196: dt=331.776000, rms=0.578 (0.727%), neg=0, invalid=762 0197: dt=103.680000, rms=0.576 (0.411%), neg=0, invalid=762 0198: dt=115.568345, rms=0.573 (0.582%), neg=0, invalid=762 0199: dt=36.288000, rms=0.572 (0.142%), neg=0, invalid=762 0200: dt=145.152000, rms=0.571 (0.171%), neg=0, invalid=762 0201: dt=145.152000, rms=0.568 (0.418%), neg=0, invalid=762 0202: dt=36.288000, rms=0.568 (0.120%), neg=0, invalid=762 0203: dt=124.416000, rms=0.567 (0.076%), neg=0, invalid=762 0204: dt=145.152000, rms=0.565 (0.361%), neg=0, invalid=762 0205: dt=36.288000, rms=0.565 (0.070%), neg=0, invalid=762 0206: dt=145.152000, rms=0.564 (0.086%), neg=0, invalid=762 0207: dt=145.152000, rms=0.563 (0.289%), neg=0, invalid=762 0208: dt=36.288000, rms=0.562 (0.072%), neg=0, invalid=762 0209: dt=124.416000, rms=0.562 (0.055%), neg=0, invalid=762 0210: dt=145.152000, rms=0.561 (0.246%), neg=0, invalid=762 0211: dt=31.104000, rms=0.560 (0.039%), neg=0, invalid=762 0212: dt=31.104000, rms=0.560 (0.015%), neg=0, invalid=762 0213: dt=31.104000, rms=0.560 (0.024%), neg=0, invalid=762 0214: dt=31.104000, rms=0.560 (0.059%), neg=0, invalid=762 0215: dt=31.104000, rms=0.559 (0.110%), neg=0, invalid=762 0216: dt=31.104000, rms=0.559 (0.138%), neg=0, invalid=762 0217: dt=31.104000, rms=0.558 (0.138%), neg=0, invalid=762 0218: dt=31.104000, rms=0.557 (0.140%), neg=0, invalid=762 0219: dt=31.104000, rms=0.556 (0.128%), neg=0, invalid=762 0220: dt=31.104000, rms=0.556 (0.122%), neg=0, invalid=762 0221: dt=31.104000, rms=0.555 (0.119%), neg=0, invalid=762 0222: dt=31.104000, rms=0.554 (0.130%), neg=0, invalid=762 0223: dt=31.104000, rms=0.553 (0.146%), neg=0, invalid=762 0224: dt=31.104000, rms=0.553 (0.143%), neg=0, invalid=762 0225: dt=31.104000, rms=0.552 (0.140%), neg=0, invalid=762 0226: dt=31.104000, rms=0.551 (0.118%), neg=0, invalid=762 0227: dt=31.104000, rms=0.551 (0.107%), neg=0, invalid=762 0228: dt=31.104000, rms=0.550 (0.102%), neg=0, invalid=762 0229: dt=31.104000, rms=0.549 (0.100%), neg=0, invalid=762 0230: dt=31.104000, rms=0.549 (0.105%), neg=0, invalid=762 0231: dt=31.104000, rms=0.548 (0.112%), neg=0, invalid=762 0232: dt=31.104000, rms=0.548 (0.102%), neg=0, invalid=762 0233: dt=31.104000, rms=0.547 (0.092%), neg=0, invalid=762 0234: dt=31.104000, rms=0.547 (0.091%), neg=0, invalid=762 0235: dt=31.104000, rms=0.546 (0.088%), neg=0, invalid=762 0236: dt=31.104000, rms=0.546 (0.080%), neg=0, invalid=762 0237: dt=31.104000, rms=0.545 (0.073%), neg=0, invalid=762 0238: dt=31.104000, rms=0.545 (0.081%), neg=0, invalid=762 0239: dt=31.104000, rms=0.545 (0.079%), neg=0, invalid=762 0240: dt=31.104000, rms=0.544 (0.075%), neg=0, invalid=762 0241: dt=31.104000, rms=0.544 (0.069%), neg=0, invalid=762 0242: dt=31.104000, rms=0.543 (0.062%), neg=0, invalid=762 0243: dt=31.104000, rms=0.543 (0.065%), neg=0, invalid=762 0244: dt=31.104000, rms=0.543 (0.069%), neg=0, invalid=762 0245: dt=31.104000, rms=0.542 (0.062%), neg=0, invalid=762 0246: dt=31.104000, rms=0.542 (0.063%), neg=0, invalid=762 0247: dt=31.104000, rms=0.542 (0.058%), neg=0, invalid=762 0248: dt=31.104000, rms=0.541 (0.055%), neg=0, invalid=762 0249: dt=31.104000, rms=0.541 (0.050%), neg=0, invalid=762 0250: dt=31.104000, rms=0.541 (0.049%), neg=0, invalid=762 0251: dt=31.104000, rms=0.541 (0.044%), neg=0, invalid=762 0252: dt=31.104000, rms=0.540 (0.049%), neg=0, invalid=762 0253: dt=31.104000, rms=0.540 (0.050%), neg=0, invalid=762 0254: dt=31.104000, rms=0.540 (0.052%), neg=0, invalid=762 0255: dt=31.104000, rms=0.540 (0.053%), neg=0, invalid=762 0256: dt=31.104000, rms=0.539 (0.046%), neg=0, invalid=762 0257: dt=31.104000, rms=0.539 (0.040%), neg=0, invalid=762 0258: dt=31.104000, rms=0.539 (0.040%), neg=0, invalid=762 0259: dt=31.104000, rms=0.539 (0.034%), neg=0, invalid=762 0260: dt=31.104000, rms=0.538 (0.038%), neg=0, invalid=762 0261: dt=31.104000, rms=0.538 (0.037%), neg=0, invalid=762 0262: dt=31.104000, rms=0.538 (0.041%), neg=0, invalid=762 0263: dt=31.104000, rms=0.538 (0.039%), neg=0, invalid=762 0264: dt=31.104000, rms=0.538 (0.038%), neg=0, invalid=762 0265: dt=31.104000, rms=0.537 (0.038%), neg=0, invalid=762 0266: dt=31.104000, rms=0.537 (0.035%), neg=0, invalid=762 0267: dt=31.104000, rms=0.537 (0.034%), neg=0, invalid=762 0268: dt=31.104000, rms=0.537 (0.034%), neg=0, invalid=762 0269: dt=31.104000, rms=0.537 (0.033%), neg=0, invalid=762 0270: dt=31.104000, rms=0.537 (0.031%), neg=0, invalid=762 0271: dt=31.104000, rms=0.536 (0.027%), neg=0, invalid=762 0272: dt=31.104000, rms=0.536 (0.027%), neg=0, invalid=762 0273: dt=31.104000, rms=0.536 (0.026%), neg=0, invalid=762 0274: dt=31.104000, rms=0.536 (0.025%), neg=0, invalid=762 0275: dt=31.104000, rms=0.536 (0.029%), neg=0, invalid=762 0276: dt=31.104000, rms=0.536 (0.028%), neg=0, invalid=762 0277: dt=31.104000, rms=0.536 (0.028%), neg=0, invalid=762 0278: dt=31.104000, rms=0.535 (0.025%), neg=0, invalid=762 0279: dt=31.104000, rms=0.535 (0.021%), neg=0, invalid=762 0280: dt=31.104000, rms=0.535 (0.023%), neg=0, invalid=762 0281: dt=31.104000, rms=0.535 (0.023%), neg=0, invalid=762 0282: dt=31.104000, rms=0.535 (0.020%), neg=0, invalid=762 0283: dt=580.608000, rms=0.535 (0.021%), neg=0, invalid=762 0284: dt=36.288000, rms=0.535 (0.018%), neg=0, invalid=762 0285: dt=36.288000, rms=0.535 (0.007%), neg=0, invalid=762 0286: dt=36.288000, rms=0.535 (0.005%), neg=0, invalid=762 0287: dt=36.288000, rms=0.535 (0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.535, neg=0, invalid=762 0288: dt=145.152000, rms=0.532 (0.500%), neg=0, invalid=762 0289: dt=36.288000, rms=0.531 (0.130%), neg=0, invalid=762 0290: dt=124.416000, rms=0.531 (0.069%), neg=0, invalid=762 0291: dt=124.416000, rms=0.531 (0.084%), neg=0, invalid=762 0292: dt=36.288000, rms=0.530 (0.036%), neg=0, invalid=762 0293: dt=36.288000, rms=0.530 (0.016%), neg=0, invalid=762 0294: dt=36.288000, rms=0.530 (0.023%), neg=0, invalid=762 0295: dt=36.288000, rms=0.530 (0.036%), neg=0, invalid=762 0296: dt=36.288000, rms=0.530 (0.043%), neg=0, invalid=762 0297: dt=36.288000, rms=0.530 (0.051%), neg=0, invalid=762 0298: dt=36.288000, rms=0.529 (0.051%), neg=0, invalid=762 0299: dt=36.288000, rms=0.529 (0.052%), neg=0, invalid=762 0300: dt=36.288000, rms=0.529 (0.048%), neg=0, invalid=762 0301: dt=36.288000, rms=0.528 (0.046%), neg=0, invalid=762 0302: dt=36.288000, rms=0.528 (0.048%), neg=0, invalid=762 0303: dt=36.288000, rms=0.528 (0.049%), neg=0, invalid=762 0304: dt=36.288000, rms=0.528 (0.046%), neg=0, invalid=762 0305: dt=36.288000, rms=0.528 (0.043%), neg=0, invalid=762 0306: dt=36.288000, rms=0.527 (0.042%), neg=0, invalid=762 0307: dt=36.288000, rms=0.527 (0.041%), neg=0, invalid=762 0308: dt=36.288000, rms=0.527 (0.040%), neg=0, invalid=762 0309: dt=36.288000, rms=0.527 (0.036%), neg=0, invalid=762 0310: dt=36.288000, rms=0.526 (0.035%), neg=0, invalid=762 0311: dt=36.288000, rms=0.526 (0.036%), neg=0, invalid=762 0312: dt=36.288000, rms=0.526 (0.033%), neg=0, invalid=762 0313: dt=36.288000, rms=0.526 (0.033%), neg=0, invalid=762 0314: dt=36.288000, rms=0.526 (0.030%), neg=0, invalid=762 0315: dt=36.288000, rms=0.526 (0.028%), neg=0, invalid=762 0316: dt=36.288000, rms=0.525 (0.029%), neg=0, invalid=762 0317: dt=36.288000, rms=0.525 (0.025%), neg=0, invalid=762 0318: dt=36.288000, rms=0.525 (0.025%), neg=0, invalid=762 0319: dt=36.288000, rms=0.525 (0.022%), neg=0, invalid=762 0320: dt=36.288000, rms=0.525 (0.025%), neg=0, invalid=762 0321: dt=36.288000, rms=0.525 (0.028%), neg=0, invalid=762 0322: dt=36.288000, rms=0.525 (0.027%), neg=0, invalid=762 0323: dt=36.288000, rms=0.525 (0.026%), neg=0, invalid=762 0324: dt=36.288000, rms=0.524 (0.021%), neg=0, invalid=762 0325: dt=36.288000, rms=0.524 (0.024%), neg=0, invalid=762 0326: dt=36.288000, rms=0.524 (0.026%), neg=0, invalid=762 0327: dt=36.288000, rms=0.524 (0.023%), neg=0, invalid=762 0328: dt=36.288000, rms=0.524 (0.018%), neg=0, invalid=762 0329: dt=82.944000, rms=0.524 (0.002%), neg=0, invalid=762 0330: dt=82.944000, rms=0.524 (0.011%), neg=0, invalid=762 0331: dt=82.944000, rms=0.524 (0.007%), neg=0, invalid=762 0332: dt=82.944000, rms=0.524 (0.008%), neg=0, invalid=762 0333: dt=82.944000, rms=0.524 (0.018%), neg=0, invalid=762 0334: dt=82.944000, rms=0.524 (0.013%), neg=0, invalid=762 setting smoothness coefficient to 0.118 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.532, neg=0, invalid=762 0335: dt=11.200000, rms=0.531 (0.106%), neg=0, invalid=762 0336: dt=11.200000, rms=0.531 (0.055%), neg=0, invalid=762 0337: dt=25.600000, rms=0.530 (0.068%), neg=0, invalid=762 0338: dt=44.800000, rms=0.529 (0.255%), neg=0, invalid=762 0339: dt=153.600000, rms=0.527 (0.493%), neg=0, invalid=762 0340: dt=11.200000, rms=0.525 (0.234%), neg=0, invalid=762 0341: dt=2.800000, rms=0.525 (0.059%), neg=0, invalid=762 0342: dt=2.800000, rms=0.525 (0.053%), neg=0, invalid=762 0343: dt=0.700000, rms=0.525 (0.011%), neg=0, invalid=762 0344: dt=0.175000, rms=0.525 (0.005%), neg=0, invalid=762 0345: dt=0.087500, rms=0.525 (0.002%), neg=0, invalid=762 0346: dt=0.043750, rms=0.525 (0.001%), neg=0, invalid=762 0347: dt=0.010937, rms=0.525 (-0.001%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.525, neg=0, invalid=762 0348: dt=54.964706, rms=0.519 (1.046%), neg=0, invalid=762 0349: dt=25.025641, rms=0.518 (0.321%), neg=0, invalid=762 0350: dt=44.800000, rms=0.516 (0.309%), neg=0, invalid=762 0351: dt=32.000000, rms=0.515 (0.156%), neg=0, invalid=762 0352: dt=32.000000, rms=0.515 (0.153%), neg=0, invalid=762 0353: dt=32.000000, rms=0.514 (0.133%), neg=0, invalid=762 0354: dt=32.000000, rms=0.513 (0.127%), neg=0, invalid=762 0355: dt=25.600000, rms=0.513 (0.113%), neg=0, invalid=762 0356: dt=44.800000, rms=0.512 (0.118%), neg=0, invalid=762 0357: dt=25.600000, rms=0.511 (0.110%), neg=0, invalid=762 0358: dt=38.400000, rms=0.511 (0.097%), neg=0, invalid=762 0359: dt=25.600000, rms=0.510 (0.097%), neg=0, invalid=762 0360: dt=38.400000, rms=0.510 (0.087%), neg=0, invalid=762 0361: dt=25.600000, rms=0.510 (0.098%), neg=0, invalid=762 0362: dt=38.400000, rms=0.509 (0.068%), neg=0, invalid=762 0363: dt=25.600000, rms=0.509 (0.091%), neg=0, invalid=762 0364: dt=32.000000, rms=0.508 (0.058%), neg=0, invalid=762 0365: dt=38.400000, rms=0.508 (0.090%), neg=0, invalid=762 0366: dt=19.200000, rms=0.508 (0.049%), neg=0, invalid=762 0367: dt=19.200000, rms=0.507 (0.054%), neg=0, invalid=762 0368: dt=19.200000, rms=0.507 (0.072%), neg=0, invalid=762 0369: dt=19.200000, rms=0.507 (0.035%), neg=0, invalid=762 0370: dt=19.200000, rms=0.507 (0.039%), neg=0, invalid=762 0371: dt=19.200000, rms=0.506 (0.066%), neg=0, invalid=762 0372: dt=19.200000, rms=0.506 (0.095%), neg=0, invalid=762 0373: dt=19.200000, rms=0.505 (0.116%), neg=0, invalid=762 0374: dt=19.200000, rms=0.505 (0.035%), neg=0, invalid=762 0375: dt=4.800000, rms=0.505 (0.005%), neg=0, invalid=762 0376: dt=2.400000, rms=0.505 (0.005%), neg=0, invalid=762 0377: dt=2.000000, rms=0.505 (0.003%), neg=0, invalid=762 0378: dt=0.250000, rms=0.505 (0.001%), neg=0, invalid=762 0379: dt=0.007812, rms=0.505 (0.000%), neg=0, invalid=762 0380: dt=0.001953, rms=0.505 (0.000%), neg=0, invalid=762 setting smoothness coefficient to 0.400 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.520, neg=0, invalid=762 0381: dt=0.000000, rms=0.520 (0.041%), neg=0, invalid=762 0382: dt=0.000000, rms=0.520 (0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.520, neg=0, invalid=762 0383: dt=0.000000, rms=0.520 (0.041%), neg=0, invalid=762 0384: dt=0.000000, rms=0.520 (0.000%), neg=0, invalid=762 setting smoothness coefficient to 1.000 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.549, neg=0, invalid=762 0385: dt=1.811024, rms=0.545 (0.741%), neg=0, invalid=762 0386: dt=0.448000, rms=0.545 (0.033%), neg=0, invalid=762 0387: dt=0.448000, rms=0.545 (0.010%), neg=0, invalid=762 0388: dt=0.448000, rms=0.545 (-0.038%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.545, neg=0, invalid=762 0389: dt=1.792000, rms=0.544 (0.303%), neg=0, invalid=762 0390: dt=1.024000, rms=0.544 (0.023%), neg=0, invalid=762 0391: dt=1.024000, rms=0.544 (-0.012%), neg=0, invalid=762 resetting metric properties... setting smoothness coefficient to 2.000 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.516, neg=0, invalid=762 0392: dt=0.448000, rms=0.503 (2.407%), neg=0, invalid=762 0393: dt=0.448000, rms=0.500 (0.554%), neg=0, invalid=762 0394: dt=0.448000, rms=0.499 (0.326%), neg=0, invalid=762 0395: dt=0.448000, rms=0.498 (0.198%), neg=0, invalid=762 0396: dt=0.461538, rms=0.497 (0.153%), neg=0, invalid=762 0397: dt=0.448000, rms=0.496 (0.101%), neg=0, invalid=762 0398: dt=0.448000, rms=0.496 (0.086%), neg=0, invalid=762 0399: dt=0.448000, rms=0.496 (0.060%), neg=0, invalid=762 0400: dt=0.448000, rms=0.495 (0.057%), neg=0, invalid=762 0401: dt=0.448000, rms=0.495 (0.038%), neg=0, invalid=762 0402: dt=0.448000, rms=0.495 (0.042%), neg=0, invalid=762 0403: dt=0.448000, rms=0.495 (0.062%), neg=0, invalid=762 0404: dt=0.448000, rms=0.494 (0.071%), neg=0, invalid=762 0405: dt=0.448000, rms=0.494 (0.080%), neg=0, invalid=762 0406: dt=0.448000, rms=0.494 (0.072%), neg=0, invalid=762 0407: dt=0.448000, rms=0.493 (0.048%), neg=0, invalid=762 0408: dt=0.448000, rms=0.493 (0.023%), neg=0, invalid=762 0409: dt=0.448000, rms=0.493 (0.016%), neg=0, invalid=762 0410: dt=0.112000, rms=0.493 (-0.001%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.493, neg=0, invalid=762 0411: dt=0.448000, rms=0.490 (0.776%), neg=0, invalid=762 0412: dt=0.448000, rms=0.489 (0.121%), neg=0, invalid=762 0413: dt=0.448000, rms=0.489 (0.036%), neg=0, invalid=762 0414: dt=0.448000, rms=0.489 (0.008%), neg=0, invalid=762 0415: dt=0.448000, rms=0.489 (0.007%), neg=0, invalid=762 0416: dt=0.448000, rms=0.489 (0.005%), neg=0, invalid=762 0417: dt=0.048000, rms=0.489 (0.002%), neg=0, invalid=762 label assignment complete, 0 changed (0.00%) ********************* ALLOWING NEGATIVE NODES IN DEFORMATION******************************** **************** pass 1 of 1 ************************ enabling zero nodes setting smoothness coefficient to 0.008 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.487, neg=0, invalid=762 0418: dt=0.000000, rms=0.486 (0.054%), neg=0, invalid=762 0419: dt=0.000000, rms=0.486 (0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.487, neg=0, invalid=762 0420: dt=129.472000, rms=0.486 (0.142%), neg=0, invalid=762 0421: dt=129.472000, rms=0.486 (0.029%), neg=0, invalid=762 0422: dt=129.472000, rms=0.486 (0.008%), neg=0, invalid=762 0423: dt=129.472000, rms=0.486 (0.040%), neg=0, invalid=762 0424: dt=129.472000, rms=0.486 (0.021%), neg=0, invalid=762 0425: dt=129.472000, rms=0.485 (0.031%), neg=0, invalid=762 0426: dt=129.472000, rms=0.485 (0.004%), neg=0, invalid=762 setting smoothness coefficient to 0.031 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.486, neg=0, invalid=762 0427: dt=9.072000, rms=0.485 (0.055%), neg=0, invalid=762 0428: dt=2.268000, rms=0.485 (0.001%), neg=0, invalid=762 0429: dt=2.268000, rms=0.485 (-0.001%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.486, neg=0, invalid=762 0430: dt=145.152000, rms=0.484 (0.400%), neg=0, invalid=762 0431: dt=36.288000, rms=0.483 (0.104%), neg=0, invalid=762 0432: dt=36.288000, rms=0.483 (0.044%), neg=0, invalid=762 0433: dt=36.288000, rms=0.483 (0.081%), neg=0, invalid=762 0434: dt=36.288000, rms=0.482 (0.127%), neg=0, invalid=762 0435: dt=36.288000, rms=0.481 (0.133%), neg=0, invalid=762 0436: dt=36.288000, rms=0.481 (0.135%), neg=0, invalid=762 0437: dt=36.288000, rms=0.480 (0.121%), neg=0, invalid=762 0438: dt=36.288000, rms=0.479 (0.125%), neg=0, invalid=762 0439: dt=36.288000, rms=0.479 (0.117%), neg=0, invalid=762 0440: dt=145.152000, rms=0.479 (0.045%), neg=0, invalid=762 0441: dt=145.152000, rms=0.479 (-0.075%), neg=0, invalid=762 setting smoothness coefficient to 0.118 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.479, neg=0, invalid=762 iter 0, gcam->neg = 1 after 0 iterations, nbhd size=0, neg = 0 0442: dt=24.901818, rms=0.478 (0.300%), neg=0, invalid=762 iter 0, gcam->neg = 4 after 8 iterations, nbhd size=1, neg = 0 0443: dt=44.800000, rms=0.476 (0.383%), neg=0, invalid=762 iter 0, gcam->neg = 2 after 0 iterations, nbhd size=0, neg = 0 0444: dt=38.400000, rms=0.475 (0.196%), neg=0, invalid=762 iter 0, gcam->neg = 1 after 0 iterations, nbhd size=0, neg = 0 0445: dt=38.400000, rms=0.474 (0.256%), neg=0, invalid=762 iter 0, gcam->neg = 2 after 1 iterations, nbhd size=0, neg = 0 0446: dt=38.400000, rms=0.472 (0.358%), neg=0, invalid=762 iter 0, gcam->neg = 12 after 10 iterations, nbhd size=1, neg = 0 0447: dt=38.400000, rms=0.471 (0.150%), neg=0, invalid=762 iter 0, gcam->neg = 9 after 1 iterations, nbhd size=0, neg = 0 0448: dt=38.400000, rms=0.470 (0.278%), neg=0, invalid=762 iter 0, gcam->neg = 13 after 12 iterations, nbhd size=1, neg = 0 0449: dt=38.400000, rms=0.470 (0.116%), neg=0, invalid=762 iter 0, gcam->neg = 13 after 3 iterations, nbhd size=0, neg = 0 0450: dt=38.400000, rms=0.469 (0.179%), neg=0, invalid=762 iter 0, gcam->neg = 11 after 2 iterations, nbhd size=0, neg = 0 0451: dt=38.400000, rms=0.468 (0.152%), neg=0, invalid=762 iter 0, gcam->neg = 9 after 7 iterations, nbhd size=0, neg = 0 0452: dt=38.400000, rms=0.467 (0.230%), neg=0, invalid=762 iter 0, gcam->neg = 4 after 9 iterations, nbhd size=1, neg = 0 0453: dt=38.400000, rms=0.466 (0.124%), neg=0, invalid=762 iter 0, gcam->neg = 8 after 1 iterations, nbhd size=0, neg = 0 0454: dt=38.400000, rms=0.466 (0.169%), neg=0, invalid=762 iter 0, gcam->neg = 1 after 7 iterations, nbhd size=1, neg = 0 0455: dt=38.400000, rms=0.465 (0.104%), neg=0, invalid=762 iter 0, gcam->neg = 1 after 1 iterations, nbhd size=0, neg = 0 0456: dt=38.400000, rms=0.465 (0.137%), neg=0, invalid=762 iter 0, gcam->neg = 5 after 9 iterations, nbhd size=1, neg = 0 0457: dt=38.400000, rms=0.464 (0.040%), neg=0, invalid=762 iter 0, gcam->neg = 4 after 0 iterations, nbhd size=0, neg = 0 0458: dt=38.400000, rms=0.464 (0.136%), neg=0, invalid=762 iter 0, gcam->neg = 1 after 1 iterations, nbhd size=0, neg = 0 0459: dt=38.400000, rms=0.464 (0.037%), neg=0, invalid=762 0460: dt=38.400000, rms=0.463 (0.130%), neg=0, invalid=762 iter 0, gcam->neg = 2 after 0 iterations, nbhd size=0, neg = 0 0461: dt=38.400000, rms=0.463 (0.034%), neg=0, invalid=762 iter 0, gcam->neg = 1 after 0 iterations, nbhd size=0, neg = 0 0462: dt=38.400000, rms=0.462 (0.089%), neg=0, invalid=762 iter 0, gcam->neg = 2 after 7 iterations, nbhd size=1, neg = 0 0463: dt=38.400000, rms=0.462 (-0.036%), neg=0, invalid=762 0464: dt=19.200000, rms=0.462 (0.071%), neg=0, invalid=762 0465: dt=44.800000, rms=0.462 (0.072%), neg=0, invalid=762 0466: dt=11.200000, rms=0.462 (0.003%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.462, neg=0, invalid=762 iter 0, gcam->neg = 2 after 1 iterations, nbhd size=0, neg = 0 0467: dt=72.386207, rms=0.457 (1.135%), neg=0, invalid=762 0468: dt=22.741573, rms=0.455 (0.280%), neg=0, invalid=762 0469: dt=44.800000, rms=0.455 (0.120%), neg=0, invalid=762 0470: dt=44.800000, rms=0.455 (0.000%), neg=0, invalid=762 0471: dt=44.800000, rms=0.454 (0.230%), neg=0, invalid=762 0472: dt=44.800000, rms=0.453 (0.091%), neg=0, invalid=762 iter 0, gcam->neg = 2 after 4 iterations, nbhd size=0, neg = 0 0473: dt=44.800000, rms=0.453 (-0.007%), neg=0, invalid=762 0474: dt=11.200000, rms=0.453 (0.066%), neg=0, invalid=762 0475: dt=11.200000, rms=0.453 (0.036%), neg=0, invalid=762 setting smoothness coefficient to 0.400 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.463, neg=0, invalid=762 0476: dt=1.008000, rms=0.462 (0.062%), neg=0, invalid=762 0477: dt=0.720000, rms=0.462 (0.005%), neg=0, invalid=762 0478: dt=0.720000, rms=0.462 (-0.003%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.462, neg=0, invalid=762 0479: dt=5.333333, rms=0.462 (0.191%), neg=0, invalid=762 0480: dt=4.032000, rms=0.461 (0.038%), neg=0, invalid=762 0481: dt=4.032000, rms=0.461 (0.018%), neg=0, invalid=762 iter 0, gcam->neg = 1 after 0 iterations, nbhd size=0, neg = 0 0482: dt=4.032000, rms=0.461 (-0.066%), neg=0, invalid=762 setting smoothness coefficient to 1.000 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.472, neg=0, invalid=762 0483: dt=0.256000, rms=0.472 (0.060%), neg=0, invalid=762 0484: dt=0.080000, rms=0.472 (0.001%), neg=0, invalid=762 0485: dt=0.080000, rms=0.472 (0.001%), neg=0, invalid=762 0486: dt=0.080000, rms=0.472 (-0.003%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.472, neg=0, invalid=762 0487: dt=1.280000, rms=0.471 (0.213%), neg=0, invalid=762 0488: dt=0.448000, rms=0.471 (0.020%), neg=0, invalid=762 0489: dt=0.448000, rms=0.471 (0.011%), neg=0, invalid=762 0490: dt=0.448000, rms=0.471 (-0.017%), neg=0, invalid=762 resetting metric properties... setting smoothness coefficient to 2.000 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.461, neg=0, invalid=762 iter 0, gcam->neg = 625 after 11 iterations, nbhd size=1, neg = 0 0491: dt=1.975787, rms=0.437 (5.141%), neg=0, invalid=762 0492: dt=0.028000, rms=0.437 (0.009%), neg=0, invalid=762 0493: dt=0.028000, rms=0.437 (-0.002%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.437, neg=0, invalid=762 0494: dt=0.080000, rms=0.437 (0.115%), neg=0, invalid=762 0495: dt=0.004000, rms=0.437 (0.001%), neg=0, invalid=762 0496: dt=0.004000, rms=0.437 (-0.000%), neg=0, invalid=762 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 ************************ enabling zero nodes setting smoothness coefficient to 0.008 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.424, neg=0, invalid=762 0497: dt=0.000000, rms=0.424 (0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.424, neg=0, invalid=762 0498: dt=129.472000, rms=0.424 (0.059%), neg=0, invalid=762 0499: dt=129.472000, rms=0.424 (0.010%), neg=0, invalid=762 0500: dt=129.472000, rms=0.424 (0.002%), neg=0, invalid=762 0501: dt=129.472000, rms=0.424 (0.003%), neg=0, invalid=762 0502: dt=129.472000, rms=0.424 (0.003%), neg=0, invalid=762 0503: dt=129.472000, rms=0.424 (0.000%), neg=0, invalid=762 0504: dt=129.472000, rms=0.424 (-0.005%), neg=0, invalid=762 setting smoothness coefficient to 0.031 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.424, neg=0, invalid=762 0505: dt=0.000000, rms=0.424 (0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.424, neg=0, invalid=762 0506: dt=145.152000, rms=0.424 (0.080%), neg=0, invalid=762 0507: dt=82.944000, rms=0.424 (0.047%), neg=0, invalid=762 0508: dt=82.944000, rms=0.424 (0.009%), neg=0, invalid=762 0509: dt=82.944000, rms=0.423 (0.067%), neg=0, invalid=762 0510: dt=82.944000, rms=0.423 (0.042%), neg=0, invalid=762 0511: dt=82.944000, rms=0.423 (0.047%), neg=0, invalid=762 0512: dt=82.944000, rms=0.423 (0.031%), neg=0, invalid=762 setting smoothness coefficient to 0.118 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.423, neg=0, invalid=762 0513: dt=8.000000, rms=0.423 (0.038%), neg=0, invalid=762 0514: dt=2.800000, rms=0.423 (0.003%), neg=0, invalid=762 0515: dt=2.800000, rms=0.423 (0.000%), neg=0, invalid=762 0516: dt=2.800000, rms=0.423 (-0.009%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.423, neg=0, invalid=762 0517: dt=86.207229, rms=0.420 (0.723%), neg=0, invalid=762 iter 0, gcam->neg = 1 after 0 iterations, nbhd size=0, neg = 0 0518: dt=11.200000, rms=0.419 (0.186%), neg=0, invalid=762 0519: dt=11.200000, rms=0.419 (0.059%), neg=0, invalid=762 iter 0, gcam->neg = 2 after 0 iterations, nbhd size=0, neg = 0 0520: dt=11.200000, rms=0.419 (0.049%), neg=0, invalid=762 0521: dt=11.200000, rms=0.419 (0.037%), neg=0, invalid=762 0522: dt=44.800000, rms=0.418 (0.179%), neg=0, invalid=762 0523: dt=19.200000, rms=0.418 (0.057%), neg=0, invalid=762 setting smoothness coefficient to 0.400 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.420, neg=0, invalid=762 0524: dt=2.880000, rms=0.420 (0.028%), neg=0, invalid=762 0525: dt=1.008000, rms=0.420 (0.002%), neg=0, invalid=762 iter 0, gcam->neg = 2 after 1 iterations, nbhd size=0, neg = 0 0526: dt=1.008000, rms=0.420 (-0.002%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.420, neg=0, invalid=762 iter 0, gcam->neg = 6 after 2 iterations, nbhd size=0, neg = 0 0527: dt=29.119221, rms=0.418 (0.595%), neg=0, invalid=762 iter 0, gcam->neg = 3 after 10 iterations, nbhd size=1, neg = 0 0528: dt=11.520000, rms=0.417 (0.222%), neg=0, invalid=762 0529: dt=11.520000, rms=0.417 (0.064%), neg=0, invalid=762 iter 0, gcam->neg = 1 after 0 iterations, nbhd size=0, neg = 0 0530: dt=11.520000, rms=0.416 (0.087%), neg=0, invalid=762 iter 0, gcam->neg = 1 after 0 iterations, nbhd size=0, neg = 0 0531: dt=11.520000, rms=0.416 (0.135%), neg=0, invalid=762 0532: dt=11.520000, rms=0.415 (0.094%), neg=0, invalid=762 iter 0, gcam->neg = 3 after 4 iterations, nbhd size=0, neg = 0 0533: dt=11.520000, rms=0.415 (0.103%), neg=0, invalid=762 iter 0, gcam->neg = 9 after 10 iterations, nbhd size=1, neg = 0 0534: dt=11.520000, rms=0.415 (0.078%), neg=0, invalid=762 iter 0, gcam->neg = 1 after 0 iterations, nbhd size=0, neg = 0 0535: dt=6.000000, rms=0.414 (0.011%), neg=0, invalid=762 0536: dt=6.000000, rms=0.414 (0.006%), neg=0, invalid=762 0537: dt=6.000000, rms=0.414 (0.002%), neg=0, invalid=762 0538: dt=6.000000, rms=0.414 (-0.005%), neg=0, invalid=762 setting smoothness coefficient to 1.000 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.420, neg=0, invalid=762 0539: dt=0.000000, rms=0.420 (0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.420, neg=0, invalid=762 0540: dt=0.000000, rms=0.420 (0.000%), neg=0, invalid=762 resetting metric properties... setting smoothness coefficient to 2.000 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=0.410, neg=0, invalid=762 iter 0, gcam->neg = 399 after 15 iterations, nbhd size=1, neg = 0 0541: dt=1.280000, rms=0.403 (1.818%), neg=0, invalid=762 0542: dt=0.000020, rms=0.403 (0.000%), neg=0, invalid=762 0543: dt=0.000020, rms=0.403 (-0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=0.403, neg=0, invalid=762 0544: dt=0.112000, rms=0.403 (0.067%), neg=0, invalid=762 0545: dt=0.096000, rms=0.403 (0.020%), neg=0, invalid=762 0546: dt=0.096000, rms=0.403 (0.008%), neg=0, invalid=762 0547: dt=0.096000, rms=0.403 (-0.038%), neg=0, invalid=762 writing output transformation to transforms/talairach.m3z... GCAMwrite mri_ca_register took 3 hours, 3 minutes and 40 seconds. mri_ca_register utimesec 10983.344277 mri_ca_register stimesec 8.196753 mri_ca_register ru_maxrss 1338808 mri_ca_register ru_ixrss 0 mri_ca_register ru_idrss 0 mri_ca_register ru_isrss 0 mri_ca_register ru_minflt 5849724 mri_ca_register ru_majflt 44 mri_ca_register ru_nswap 0 mri_ca_register ru_inblock 8496 mri_ca_register ru_oublock 63352 mri_ca_register ru_msgsnd 0 mri_ca_register ru_msgrcv 0 mri_ca_register ru_nsignals 0 mri_ca_register ru_nvcsw 60 mri_ca_register ru_nivcsw 1115106 FSRUNTIME@ mri_ca_register 3.0611 hours 1 threads #-------------------------------------- #@# SubCort Seg Mon Sep 11 13:37:31 CEST 2017 mri_ca_label -relabel_unlikely 9 .3 -prior 0.5 -align norm.mgz transforms/talairach.m3z /usr/local/freesurfer/average/RB_all_2016-05-10.vc700.gca aseg.auto_noCCseg.mgz sysname Linux hostname lugh.fisica.uniud.it machine x86_64 setenv SUBJECTS_DIR /home/gc/study/recon-all cd /home/gc/study/recon-all/400614bash/mri mri_ca_label -relabel_unlikely 9 .3 -prior 0.5 -align norm.mgz transforms/talairach.m3z /usr/local/freesurfer/average/RB_all_2016-05-10.vc700.gca aseg.auto_noCCseg.mgz == Number of threads available to mri_ca_label for OpenMP = 1 == relabeling unlikely voxels with window_size = 9 and prior threshold 0.30 using Gibbs prior factor = 0.500 renormalizing sequences with structure alignment, equivalent to: -renormalize -renormalize_mean 0.500 -regularize 0.500 reading 1 input volumes reading classifier array from /usr/local/freesurfer/average/RB_all_2016-05-10.vc700.gca reading input volume from norm.mgz average std[0] = 7.3 reading transform from transforms/talairach.m3z setting orig areas to linear transform determinant scaled 7.17 Atlas used for the 3D morph was /usr/local/freesurfer/average/RB_all_2016-05-10.vc700.gca average std = 7.3 using min determinant for regularization = 5.3 0 singular and 0 ill-conditioned covariance matrices regularized labeling volume... renormalizing by structure alignment.... renormalizing input #0 gca peak = 0.16259 (20) mri peak = 0.14490 (32) Left_Lateral_Ventricle (4): linear fit = 1.68 x + 0.0 (592 voxels, overlap=0.051) Left_Lateral_Ventricle (4): linear fit = 1.50 x + 0.0 (592 voxels, peak = 34), gca=30.0 gca peak = 0.17677 (13) mri peak = 0.15549 (33) Right_Lateral_Ventricle (43): linear fit = 2.31 x + 0.0 (327 voxels, overlap=0.028) Right_Lateral_Ventricle (43): linear fit = 1.50 x + 0.0 (327 voxels, peak = 30), gca=19.5 gca peak = 0.28129 (95) mri peak = 0.14286 (99) Right_Pallidum (52): linear fit = 1.03 x + 0.0 (942 voxels, overlap=1.011) Right_Pallidum (52): linear fit = 1.03 x + 0.0 (942 voxels, peak = 98), gca=98.3 gca peak = 0.16930 (96) mri peak = 0.15706 (99) Left_Pallidum (13): linear fit = 1.04 x + 0.0 (885 voxels, overlap=0.743) Left_Pallidum (13): linear fit = 1.04 x + 0.0 (885 voxels, peak = 100), gca=100.3 gca peak = 0.24553 (55) mri peak = 0.12948 (74) Right_Hippocampus (53): linear fit = 1.32 x + 0.0 (1156 voxels, overlap=0.017) Right_Hippocampus (53): linear fit = 1.32 x + 0.0 (1156 voxels, peak = 72), gca=72.3 gca peak = 0.30264 (59) mri peak = 0.15202 (75) Left_Hippocampus (17): linear fit = 1.27 x + 0.0 (1014 voxels, overlap=0.016) Left_Hippocampus (17): linear fit = 1.27 x + 0.0 (1014 voxels, peak = 75), gca=75.2 gca peak = 0.07580 (103) mri peak = 0.14046 (102) Right_Cerebral_White_Matter (41): linear fit = 1.00 x + 0.0 (37703 voxels, overlap=0.703) Right_Cerebral_White_Matter (41): linear fit = 1.00 x + 0.0 (37703 voxels, peak = 102), gca=102.5 gca peak = 0.07714 (104) mri peak = 0.14053 (103) Left_Cerebral_White_Matter (2): linear fit = 1.00 x + 0.0 (41633 voxels, overlap=0.642) Left_Cerebral_White_Matter (2): linear fit = 1.00 x + 0.0 (41633 voxels, peak = 103), gca=103.5 gca peak = 0.09712 (58) mri peak = 0.04183 (72) Left_Cerebral_Cortex (3): linear fit = 1.35 x + 0.0 (33943 voxels, overlap=0.003) Left_Cerebral_Cortex (3): linear fit = 1.35 x + 0.0 (33943 voxels, peak = 78), gca=78.0 gca peak = 0.11620 (58) mri peak = 0.04398 (78) Right_Cerebral_Cortex (42): linear fit = 1.33 x + 0.0 (33673 voxels, overlap=0.000) Right_Cerebral_Cortex (42): linear fit = 1.33 x + 0.0 (33673 voxels, peak = 77), gca=76.9 gca peak = 0.30970 (66) mri peak = 0.16140 (85) Right_Caudate (50): linear fit = 1.24 x + 0.0 (851 voxels, overlap=0.020) Right_Caudate (50): linear fit = 1.24 x + 0.0 (851 voxels, peak = 82), gca=81.5 gca peak = 0.15280 (69) mri peak = 0.15765 (87) Left_Caudate (11): linear fit = 1.13 x + 0.0 (846 voxels, overlap=0.017) Left_Caudate (11): linear fit = 1.13 x + 0.0 (846 voxels, peak = 78), gca=78.3 gca peak = 0.13902 (56) mri peak = 0.07409 (78) Left_Cerebellum_Cortex (8): linear fit = 1.38 x + 0.0 (33899 voxels, overlap=0.001) Left_Cerebellum_Cortex (8): linear fit = 1.38 x + 0.0 (33899 voxels, peak = 77), gca=77.0 gca peak = 0.14777 (55) mri peak = 0.07395 (77) Right_Cerebellum_Cortex (47): linear fit = 1.38 x + 0.0 (35954 voxels, overlap=0.001) Right_Cerebellum_Cortex (47): linear fit = 1.38 x + 0.0 (35954 voxels, peak = 76), gca=75.6 gca peak = 0.16765 (84) mri peak = 0.12261 (91) Left_Cerebellum_White_Matter (7): linear fit = 1.09 x + 0.0 (6165 voxels, overlap=0.404) Left_Cerebellum_White_Matter (7): linear fit = 1.09 x + 0.0 (6165 voxels, peak = 91), gca=91.1 gca peak = 0.18739 (84) mri peak = 0.16558 (91) Right_Cerebellum_White_Matter (46): linear fit = 1.09 x + 0.0 (6003 voxels, overlap=0.138) Right_Cerebellum_White_Matter (46): linear fit = 1.09 x + 0.0 (6003 voxels, peak = 91), gca=91.1 gca peak = 0.29869 (57) mri peak = 0.15917 (78) Left_Amygdala (18): linear fit = 1.35 x + 0.0 (578 voxels, overlap=0.049) Left_Amygdala (18): linear fit = 1.35 x + 0.0 (578 voxels, peak = 77), gca=76.7 gca peak = 0.33601 (57) mri peak = 0.13827 (78) Right_Amygdala (54): linear fit = 1.38 x + 0.0 (606 voxels, overlap=0.042) Right_Amygdala (54): linear fit = 1.38 x + 0.0 (606 voxels, peak = 78), gca=78.4 gca peak = 0.11131 (90) mri peak = 0.10392 (95) Left_Thalamus_Proper (10): linear fit = 1.07 x + 0.0 (5081 voxels, overlap=0.527) Left_Thalamus_Proper (10): linear fit = 1.07 x + 0.0 (5081 voxels, peak = 96), gca=95.9 gca peak = 0.11793 (83) mri peak = 0.09530 (93) Right_Thalamus_Proper (49): linear fit = 1.13 x + 0.0 (4479 voxels, overlap=0.186) Right_Thalamus_Proper (49): linear fit = 1.13 x + 0.0 (4479 voxels, peak = 94), gca=94.2 gca peak = 0.08324 (81) mri peak = 0.12714 (88) Left_Putamen (12): linear fit = 1.12 x + 0.0 (2040 voxels, overlap=0.209) Left_Putamen (12): linear fit = 1.12 x + 0.0 (2040 voxels, peak = 90), gca=90.3 gca peak = 0.10360 (77) mri peak = 0.11973 (88) Right_Putamen (51): linear fit = 1.12 x + 0.0 (2227 voxels, overlap=0.176) Right_Putamen (51): linear fit = 1.12 x + 0.0 (2227 voxels, peak = 87), gca=86.6 gca peak = 0.08424 (78) mri peak = 0.07703 (88) Brain_Stem (16): linear fit = 1.11 x + 0.0 (13423 voxels, overlap=0.476) Brain_Stem (16): linear fit = 1.11 x + 0.0 (13423 voxels, peak = 86), gca=86.2 gca peak = 0.12631 (89) mri peak = 0.08980 (99) Right_VentralDC (60): linear fit = 1.12 x + 0.0 (1716 voxels, overlap=0.209) Right_VentralDC (60): linear fit = 1.12 x + 0.0 (1716 voxels, peak = 100), gca=100.1 gca peak = 0.14500 (87) mri peak = 0.08927 (98) Left_VentralDC (28): linear fit = 1.12 x + 0.0 (1771 voxels, overlap=0.330) Left_VentralDC (28): linear fit = 1.12 x + 0.0 (1771 voxels, peak = 97), gca=97.0 gca peak = 0.14975 (24) mri peak = 0.10121 (32) gca peak = 0.19357 (14) mri peak = 0.16162 (32) Fourth_Ventricle (15): linear fit = 2.07 x + 0.0 (738 voxels, overlap=0.074) Fourth_Ventricle (15): linear fit = 2.07 x + 0.0 (738 voxels, peak = 29), gca=28.9 gca peak Unknown = 0.94835 ( 0) gca peak Left_Inf_Lat_Vent = 0.16825 (27) gca peak Left_Thalamus = 1.00000 (94) gca peak Third_Ventricle = 0.14975 (24) gca peak Fourth_Ventricle = 0.19357 (14) gca peak CSF = 0.23379 (36) gca peak Left_Accumbens_area = 0.70037 (62) gca peak Left_undetermined = 1.00000 (26) gca peak Left_vessel = 0.75997 (52) gca peak Left_choroid_plexus = 0.12089 (35) gca peak Right_Inf_Lat_Vent = 0.24655 (23) gca peak Right_Accumbens_area = 0.45042 (65) gca peak Right_vessel = 0.82168 (52) gca peak Right_choroid_plexus = 0.14516 (37) gca peak Fifth_Ventricle = 0.65475 (32) gca peak WM_hypointensities = 0.07854 (76) gca peak non_WM_hypointensities = 0.08491 (43) gca peak Optic_Chiasm = 0.71127 (75) not using caudate to estimate GM means estimating mean gm scale to be 1.33 x + 0.0 estimating mean wm scale to be 1.00 x + 0.0 estimating mean csf scale to be 1.50 x + 0.0 Left_Pallidum too bright - rescaling by 0.996 (from 1.045) to 99.9 (was 100.3) saving intensity scales to aseg.auto_noCCseg.label_intensities.txt renormalizing by structure alignment.... renormalizing input #0 gca peak = 0.12544 (31) mri peak = 0.14490 (32) Left_Lateral_Ventricle (4): linear fit = 1.14 x + 0.0 (592 voxels, overlap=0.566) Left_Lateral_Ventricle (4): linear fit = 1.14 x + 0.0 (592 voxels, peak = 35), gca=35.5 gca peak = 0.13981 (19) mri peak = 0.15549 (33) Right_Lateral_Ventricle (43): linear fit = 1.60 x + 0.0 (327 voxels, overlap=0.201) Right_Lateral_Ventricle (43): linear fit = 1.50 x + 0.0 (327 voxels, peak = 30), gca=28.5 gca peak = 0.27866 (99) mri peak = 0.14286 (99) Right_Pallidum (52): linear fit = 1.00 x + 0.0 (942 voxels, overlap=1.008) Right_Pallidum (52): linear fit = 1.00 x + 0.0 (942 voxels, peak = 99), gca=99.5 gca peak = 0.15311 (99) mri peak = 0.15706 (99) Left_Pallidum (13): linear fit = 1.00 x + 0.0 (885 voxels, overlap=0.996) Left_Pallidum (13): linear fit = 1.00 x + 0.0 (885 voxels, peak = 99), gca=99.0 gca peak = 0.23715 (73) mri peak = 0.12948 (74) Right_Hippocampus (53): linear fit = 1.00 x + 0.0 (1156 voxels, overlap=0.998) Right_Hippocampus (53): linear fit = 1.00 x + 0.0 (1156 voxels, peak = 73), gca=73.0 gca peak = 0.23896 (72) mri peak = 0.15202 (75) Left_Hippocampus (17): linear fit = 0.99 x + 0.0 (1014 voxels, overlap=1.000) Left_Hippocampus (17): linear fit = 0.99 x + 0.0 (1014 voxels, peak = 71), gca=70.9 gca peak = 0.07845 (102) mri peak = 0.14046 (102) Right_Cerebral_White_Matter (41): linear fit = 1.00 x + 0.0 (37703 voxels, overlap=0.698) Right_Cerebral_White_Matter (41): linear fit = 1.00 x + 0.0 (37703 voxels, peak = 101), gca=101.5 gca peak = 0.08042 (104) mri peak = 0.14053 (103) Left_Cerebral_White_Matter (2): linear fit = 1.00 x + 0.0 (41633 voxels, overlap=0.631) Left_Cerebral_White_Matter (2): linear fit = 1.00 x + 0.0 (41633 voxels, peak = 103), gca=103.5 gca peak = 0.07332 (78) mri peak = 0.04183 (72) Left_Cerebral_Cortex (3): linear fit = 0.98 x + 0.0 (33943 voxels, overlap=0.968) Left_Cerebral_Cortex (3): linear fit = 0.98 x + 0.0 (33943 voxels, peak = 76), gca=76.1 gca peak = 0.09026 (77) mri peak = 0.04398 (78) Right_Cerebral_Cortex (42): linear fit = 1.00 x + 0.0 (33673 voxels, overlap=0.952) Right_Cerebral_Cortex (42): linear fit = 1.00 x + 0.0 (33673 voxels, peak = 77), gca=77.0 gca peak = 0.22959 (81) mri peak = 0.16140 (85) Right_Caudate (50): linear fit = 1.01 x + 0.0 (851 voxels, overlap=1.002) Right_Caudate (50): linear fit = 1.01 x + 0.0 (851 voxels, peak = 82), gca=82.2 gca peak = 0.14927 (88) mri peak = 0.15765 (87) Left_Caudate (11): linear fit = 1.01 x + 0.0 (846 voxels, overlap=0.712) Left_Caudate (11): linear fit = 1.01 x + 0.0 (846 voxels, peak = 89), gca=89.3 gca peak = 0.10522 (76) mri peak = 0.07409 (78) Left_Cerebellum_Cortex (8): linear fit = 1.00 x + 0.0 (33899 voxels, overlap=0.913) Left_Cerebellum_Cortex (8): linear fit = 1.00 x + 0.0 (33899 voxels, peak = 76), gca=76.0 gca peak = 0.11468 (75) mri peak = 0.07395 (77) Right_Cerebellum_Cortex (47): linear fit = 0.99 x + 0.0 (35954 voxels, overlap=0.915) Right_Cerebellum_Cortex (47): linear fit = 0.99 x + 0.0 (35954 voxels, peak = 74), gca=73.9 gca peak = 0.15503 (91) mri peak = 0.12261 (91) Left_Cerebellum_White_Matter (7): linear fit = 1.00 x + 0.0 (6165 voxels, overlap=0.922) Left_Cerebellum_White_Matter (7): linear fit = 1.00 x + 0.0 (6165 voxels, peak = 91), gca=90.5 gca peak = 0.14985 (91) mri peak = 0.16558 (91) Right_Cerebellum_White_Matter (46): linear fit = 0.99 x + 0.0 (6003 voxels, overlap=0.848) Right_Cerebellum_White_Matter (46): linear fit = 0.99 x + 0.0 (6003 voxels, peak = 90), gca=89.6 gca peak = 0.29162 (78) mri peak = 0.15917 (78) Left_Amygdala (18): linear fit = 0.99 x + 0.0 (578 voxels, overlap=1.004) Left_Amygdala (18): linear fit = 0.99 x + 0.0 (578 voxels, peak = 77), gca=76.8 gca peak = 0.28610 (78) mri peak = 0.13827 (78) Right_Amygdala (54): linear fit = 0.99 x + 0.0 (606 voxels, overlap=0.997) Right_Amygdala (54): linear fit = 0.99 x + 0.0 (606 voxels, peak = 77), gca=76.8 gca peak = 0.11362 (94) mri peak = 0.10392 (95) Left_Thalamus_Proper (10): linear fit = 1.00 x + 0.0 (5081 voxels, overlap=0.829) Left_Thalamus_Proper (10): linear fit = 1.00 x + 0.0 (5081 voxels, peak = 94), gca=94.0 gca peak = 0.09201 (92) mri peak = 0.09530 (93) Right_Thalamus_Proper (49): linear fit = 1.00 x + 0.0 (4479 voxels, overlap=0.911) Right_Thalamus_Proper (49): linear fit = 1.00 x + 0.0 (4479 voxels, peak = 92), gca=92.0 gca peak = 0.08274 (92) mri peak = 0.12714 (88) Left_Putamen (12): linear fit = 1.01 x + 0.0 (2040 voxels, overlap=0.720) Left_Putamen (12): linear fit = 1.01 x + 0.0 (2040 voxels, peak = 93), gca=93.4 gca peak = 0.08153 (84) mri peak = 0.11973 (88) Right_Putamen (51): linear fit = 1.02 x + 0.0 (2227 voxels, overlap=0.787) Right_Putamen (51): linear fit = 1.02 x + 0.0 (2227 voxels, peak = 86), gca=86.1 gca peak = 0.07311 (90) mri peak = 0.07703 (88) Brain_Stem (16): linear fit = 1.01 x + 0.0 (13423 voxels, overlap=0.846) Brain_Stem (16): linear fit = 1.01 x + 0.0 (13423 voxels, peak = 91), gca=91.3 gca peak = 0.10031 (99) mri peak = 0.08980 (99) Right_VentralDC (60): linear fit = 1.00 x + 0.0 (1716 voxels, overlap=0.820) Right_VentralDC (60): linear fit = 1.00 x + 0.0 (1716 voxels, peak = 99), gca=99.5 gca peak = 0.14064 (95) mri peak = 0.08927 (98) Left_VentralDC (28): linear fit = 1.00 x + 0.0 (1771 voxels, overlap=0.907) Left_VentralDC (28): linear fit = 1.00 x + 0.0 (1771 voxels, peak = 95), gca=95.5 gca peak = 0.12656 (38) mri peak = 0.10121 (32) gca peak = 0.16542 (24) mri peak = 0.16162 (32) Fourth_Ventricle (15): linear fit = 1.39 x + 0.0 (738 voxels, overlap=0.174) Fourth_Ventricle (15): linear fit = 1.39 x + 0.0 (738 voxels, peak = 33), gca=33.5 gca peak Unknown = 0.94835 ( 0) gca peak Left_Inf_Lat_Vent = 0.13499 (41) gca peak Left_Thalamus = 0.36646 (102) gca peak Third_Ventricle = 0.12656 (38) gca peak CSF = 0.15446 (55) gca peak Left_Accumbens_area = 0.59345 (71) gca peak Left_undetermined = 0.95280 (34) gca peak Left_vessel = 0.75997 (52) gca peak Left_choroid_plexus = 0.12303 (35) gca peak Right_Inf_Lat_Vent = 0.19792 (30) gca peak Right_Accumbens_area = 0.29901 (80) gca peak Right_vessel = 0.82168 (52) gca peak Right_choroid_plexus = 0.14504 (37) gca peak Fifth_Ventricle = 0.51780 (46) gca peak WM_hypointensities = 0.07811 (75) gca peak non_WM_hypointensities = 0.11534 (54) gca peak Optic_Chiasm = 0.61319 (75) not using caudate to estimate GM means estimating mean gm scale to be 0.99 x + 0.0 estimating mean wm scale to be 1.00 x + 0.0 estimating mean csf scale to be 1.35 x + 0.0 Left_Putamen too bright - rescaling by 0.988 (from 1.015) to 92.2 (was 93.4) Left_Pallidum too bright - rescaling by 1.004 (from 1.000) to 99.4 (was 99.0) Right_Pallidum too bright - rescaling by 0.999 (from 1.005) to 99.4 (was 99.5) saving intensity scales to aseg.auto_noCCseg.label_intensities.txt saving sequentially combined intensity scales to aseg.auto_noCCseg.label_intensities.txt