Freesurfer

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30089 discussions

structure of project directory for longitudinal functional analysis
by Desch, Simon 08 Aug '18

08 Aug '18

External Email - Use Caution Dear Freesurfer experts, I’m very new to Freesurfer and I’m struggling to setup my project directory for a functional analysis. I’m running a study with each subject doing two MRI sessions, i.e. before and after they perform a perceptional training at home for three month. In each session (i.e. before and after training) they do a sensory mapping task and I want to compare mapping pre- and post-training. If possible I’d like to run this analysis contrasting two groups (who performed different kinds of training). I’m about to setup the project directory structure as depicted here: https://surfer.nmr.mgh.harvard.edu/fswiki/FsFastTutorialV4.5. The first issue I stumbled across is if to put data of all pre-training measurements of all subjects in a different „Session“ ( it says "All the data collected in one functional session (or visit) are placed under the folder (the "session directory").). As far as I can see the tutorial does neither cover longitudinal within subject comparisons nor between group comparisons (using mri_glmfit). Thus, any help is highly appreciated! Thank you! Sincerely, Freesurfer version: freesurfer-Linux-centos6_x86_64-stable-pub-v6.0.0-2beb96c _____________________________________________ Simon Desch Department of Cognitive and Clinical Neuroscience Central Institute of Mental Health Square J5, 68159 Mannheim Germany Phone: +49 (0) 621 1703 6304

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Postdoctoral Fellowship in Neuroimaging (MRI & DWI)
by Meaghan Perdue 08 Aug '18

08 Aug '18

External Email - Use Caution Dear Freesurfer Community, Please consider the job opportunity below and pass along to colleagues who may be interested. *POSTDOCTORAL FELLOWSHIP IN NEUROIMAGING (MRI and DTI)* The LandiLab (PI: Nicole Landi, PhD *https://landi.lab.uconn.edu/ <https://urldefense.proofpoint.com/v2/url?u=https-3A__landi.lab.uconn.edu_&d…>*) at Haskins Laboratories *https://haskinslabs.org/ <https://haskinslabs.org/>* (which is closely affiliated with Yale and the University of Connecticut) is seeking to hire a postdoctoral research fellow. This postdoc will join a project investigating the neurobiological basis (brain structure, genetics) of reading. The successful applicant will be responsible for conducting and interpreting analyses of neuroimaging data (structural and diffusion imaging data). This position is part of a multi-site project (Haskins Laboratories, University of Houston, Baylor College of Medicine) that is aggregating and analyzing neuroimaging and genotyping data from multiple locations to explore gene-brain-behavior relationships. Applicants must have a background conducting research using MRI. The ideal candidate will also have experience with diffusion weighted imaging (DWI) and experience with advanced statistical analysis of imaging data (e.g. imaging-genetic analyses, Bayesian methods, machine learning). *For details regarding required qualifications and application procedure, please visit: https://haskinslabs.org/postdoctoral-fellowship-neuroimaging-mri-and-dti <https://haskinslabs.org/postdoctoral-fellowship-neuroimaging-mri-and-dti>* Best regards, Meaghan Perdue -- Meaghan Perdue PhD Student Developmental Psychology Neurobiology of Language University of Connecticut Bousfield A302

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surface arithmetic?
by Rockers, Elijah D. 07 Aug '18

07 Aug '18

External Email - Use Caution Hello, I have a subject with two MRIs and surface reconstructions, several years apart. I would like to directly compare these surfaces if possible, for instance, to subtract (new - old) to see a "difference surface" or something similar. Is there a way to A) Get the surfaces into the same space so they can be combined mathematically, and B) performs operations with the surfaces, a la fslmaths? Many thanks, - Eli Houston Methodist. Leading Medicine. Houston Methodist is ranked by U.S. News & World Report as the No. 1 hospital in Texas for patient care. Houston Methodist is nationally ranked in 8 specialties and is designated as a Magnet hospital for excellence in nursing. Visit us at houstonmethodist.org. Follow us at twitter.com/MethodistHosp and facebook.com/HoustonMethodist. ***CONFIDENTIALITY NOTICE*** This e-mail is the property of Houston Methodist and/or its relevant affiliates and may contain restricted and privileged material for the sole use of the intended recipient(s). Any review, use, distribution or disclosure by others is strictly prohibited. If you are not the intended recipient (or authorized to receive for the recipient), please contact the sender and delete all copies of the message. Thank you.

2 1

WM segmentation
by Ben M 07 Aug '18

07 Aug '18

External Email - Use Caution Hi, I would like to create a mask of the WM for fMRI analysis. I read a previous post in which it was suggested to get the wm segmentation and erode it, since the result will be exclusively WM. My question is why is this so? Why can I assume that getting the WM mask from the aseg file will almost certainly get me high probability WM, >0.9 for example? In most segmentation algorithms we get posterior probabilities at each voxel, so that we can then select voxels with posterior probabilities >0.90 for example. Why is freesurfer's WM segmentation so accurate that we do not need posterior probabilities? Are these very high probabilities somehow already coded in freesurfer's segmentation algorithm? Thanks, Ben

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mris_register segmentation fault while running recon-all with -cm option on a scan with .6mm isotropic voxels
by Lalonde, Francois (NIH/NIMH) [E] 07 Aug '18

07 Aug '18

External Email - Use Caution Hello FreeSurfer Developers, I am trying to run the hippocampal and amygdala subfield segmentation and take advantage of the .6mm resolution of the scan. I was able to run recon-all successfully on the scan without the -cm option. I get the following error: ------------------------------ SUBJECT nomove_xpace_06mm_tr3bcm DATE Fri Aug 3 11:58:33 EDT 2018 USER flalonde HOST cn0638 PROCESSOR x86_64 OS Linux Linux cn0638 3.10.0-693.2.2.el7.x86_64 #1 SMP Tue Sep 12 22:26:13 UTC 2017 x86_64 x86_64 x86_64 GNU/Linux $Id: recon-all,v 1.601 2017/02/08 21:17:33 greve Exp $ /data/flalonde/freesurfer_dev/bin/recon-all PWD /gpfs/gsfs4/users/CPB/3TD/6mm/subjects/nomove_xpace_06mm_tr3bcm/scripts CMD mris_register -curv -rusage /gpfs/gsfs4/users/CPB/3TD/6mm/subjects/nomove_xpace_06mm_tr3bcm/touch/rusage.mris_register.lh.dat ../surf/lh.sphere /data/flalonde/freesurfer_dev/average/lh.folding.atlas.acfb40.noaparc.i12.2016-08-02.tif ../surf/lh.sphere.reg I’ve attached a copy of the recon-all.log 1) Freesurfer version: freesurfer-linux-centos7_x86_64-dev-20180723-7bf4760 2) Platform: CentOS Linux release 7.5.1804 (Core) 3) uname -a: Linux felix.nimh.nih.gov 3.10.0-693.2.2.el7.x86_64 #1 SMP Tue Sep 12 22:26:13 UTC 2017 x86_64 x86_64 x86_64 GNU/Linux 4) recon-all.log: see attached The list mentions running a post-hoc surface deformation (https://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg47309.html) using mris_make_surfaces as a workaround but I’m not sure if this is applies in my case or what the full command might be (e.g. mris_make_surfaces subjectname lh). Thanks, François M. Lalonde, Ph.D. DNU / HGB / DIRP / NIMH 10 Center Drive, Room 4N244 Bethesda, MD 20892-1600

2 1

Getting error while extracting hippocampus volume in dev version of freesurfer
by Yubraj Gupta 07 Aug '18

07 Aug '18

External Email - Use Caution Hello Freesurfer Developers, While extracting the Hippocampus volume from the subject folder, I'm getting the following error. This file does not contain MRI parameters This file does not contain MRI parameters In an assignment A(:) = B, the number of elements in A and B must be the same. Error in segmentSubjectT1_autoEstimateAlveusML (line 1856) MATLAB:subsassignnumelmismatch @#@FSTIME 2018:08:08:01:27:03 run_segmentSubjectT1_autoEstimateAlveusML.sh N 13 e 868.58 S 607.16 U 8388.47 P 1035% M 3765176 F 0 R 23295004 W 0 c 1773466 w 3380046 I 0 O 847496 L 19.31 35.64 36.84 @#@FSLOADPOST 2018:08:08:01:41:31 run_segmentSubjectT1_autoEstimateAlveusML.sh N 13 28.36 47.98 45.74 Linux tars 3.10.0-693.11.1.el7.x86_64 #1 SMP Mon Dec 4 23:52:40 UTC 2017 x86_64 x86_64 x86_64 GNU/Linux T1 hippocampal subfields exited with ERRORS at Wed Aug 8 01:41:31 KST 2018 I've searched the list and no similar errors have been reported. Does anyone have any thought on how to troubleshoot this one? Also, I've attached the Hippo_T1.log in case it's of any use. 1) Freesurfer version: freesurfer-linux-centos7_x86_64-dev- 20180725-1793f7a 2) platform: centos-release 7centos 3) unmae -a: Linux tars 3.10.0-693.11.1.el7.x86_64 #1 SMP Mon Dec 4 23:52:40 UTC 2017 x86_64 x86_64 x86_64 GNU/Linux 4) Hippo_T1.log: see attached

1 0

XL Defect Detected
by Rockhill, Alexander P. 07 Aug '18

07 Aug '18

Hi all, I am running recon-all and the command is stuck on the output CORRECTING DEFECT 31 (vertices=8161, convex hull=3290, v0=29848) XL defect detected... It has been on that step overnight. Is there some way to ignore the defect or correct it without taking so long? This is using freesurfer 6. Thanks, Alex Rockhill Translational NeuroEngineering Laboratory Division of Neurotherapeutics, Department of Psychiatry Massachusetts General Hospital, Martinos Center 149 13th St Charlestown #2301, Boston, MA 02129

2 1

wm.mgz values
by Aaron Tanenbaum 07 Aug '18

07 Aug '18

External Email - Use Caution Hello Freesurfers. I was wondering of for the purposes of editing wm.mgz if changing voxel values to anything but 255 and 1 will be useful in anyway. If so I was wondering if you can explain to me what the following values mean and how do I use them. #define THICKEN_FILL 200 #define NBHD_FILL 210 #define VENTRICLE_FILL 220 #define DIAGONAL_FILL 230 #define DEGENERATE_FILL 240 #define OFFSET_FILTER_FILL 245 #define AUTO_FILL 250 #define PRETESS_FILL 215 #define WM_EDITED_ON_VAL 255 #define WM_EDITED_OFF_VAL 1

2 1

-- check skull stripping No such file or directory
by Renew Andrade 07 Aug '18

07 Aug '18

External Email - Use Caution Dear Community! I have an issue with recon-all in this subject. Below is the terminal output. Renes-MacBook-Air-2:~ andraderenew$ recon-all -all -s IXI_25_Guys_DTI_recon Subject Stamp: freesurfer-Darwin-OSX-stable-pub-v6.0.0-2beb96c Current Stamp: freesurfer-Darwin-OSX-stable-pub-v6.0.0-2beb96c INFO: SUBJECTS_DIR is /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir Actual FREESURFER_HOME /Applications/freesurfer -rwxrwxrwx@ 1 andraderenew staff 117313 Aug 6 06:11 /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/scripts/recon-all.log Darwin Renes-MacBook-Air-2.local 17.5.0 Darwin Kernel Version 17.5.0: Mon Mar 5 22:24:32 PST 2018; root:xnu-4570.51.1~1/RELEASE_X86_64 x86_64 #-------------------------------------------- #@# MotionCor Mon Aug 6 14:40:17 -05 2018 Found 1 runs /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/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. \n cp /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/orig/001.mgz /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/rawavg.mgz \n /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon \n mri_convert /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/rawavg.mgz /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/orig.mgz --conform \n mri_convert.bin /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/rawavg.mgz /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/orig.mgz --conform $Id: mri_convert.c,v 1.226 2016/02/26 16:15:24 mreuter Exp $ reading from /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/rawavg.mgz... TR=0.00, TE=0.00, TI=0.00, flip angle=0.00 i_ras = (-0.998725, -0.0503472, 0.00377193) j_ras = (-0.0504772, 0.994141, -0.0955763) k_ras = (-0.00106217, 0.0956448, 0.995415) changing data type from float to uchar (noscale = 0)... MRIchangeType: Building histogram Reslicing using trilinear interpolation writing to /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/orig.mgz... \n mri_add_xform_to_header -c /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/transforms/talairach.xfm /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/orig.mgz /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/orig.mgz \n INFO: extension is mgz #-------------------------------------------- #@# Talairach Mon Aug 6 14:40:26 -05 2018 /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri \n mri_nu_correct.mni --no-rescale --i orig.mgz --o orig_nu.mgz --n 1 --proto-iters 1000 --distance 50 \n /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri /Applications/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: FreeSurferEnv.csh,v 1.89 2016/06/09 14:54:31 zkaufman Exp $ Darwin Renes-MacBook-Air-2.local 17.5.0 Darwin Kernel Version 17.5.0: Mon Mar 5 22:24:32 PST 2018; root:xnu-4570.51.1~1/RELEASE_X86_64 x86_64 Mon Aug 6 14:40:26 -05 2018 Program nu_correct, built from: Package MNI N3, version 1.12.0, compiled by nicks(a)gust.nmr.mgh.harvard.edu (x86_64-apple-darwin11.4.2) on 2015-06-19 at 15:37:08 /usr/bin/bc tmpdir is ./tmp.mri_nu_correct.mni.3771 /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri mri_convert orig.mgz ./tmp.mri_nu_correct.mni.3771/nu0.mnc -odt float mri_convert.bin orig.mgz ./tmp.mri_nu_correct.mni.3771/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, -1.28057e-09, 2.32831e-10) j_ras = (-1.16415e-10, 0, -1) k_ras = (-2.38651e-09, 1, -7.45058e-09) changing data type from uchar to float (noscale = 0)... writing to ./tmp.mri_nu_correct.mni.3771/nu0.mnc... -------------------------------------------------------- Iteration 1 Mon Aug 6 14:40:31 -05 2018 nu_correct -clobber ./tmp.mri_nu_correct.mni.3771/nu0.mnc ./tmp.mri_nu_correct.mni.3771/nu1.mnc -tmpdir ./tmp.mri_nu_correct.mni.3771/0/ -iterations 1000 -distance 50 [andraderenew@Renes-MacBook-Air-2.local:/Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/] [2018-08-06 14:40:31] running: /Applications/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.3771/0/ ./tmp.mri_nu_correct.mni.3771/nu0.mnc ./tmp.mri_nu_correct.mni.3771/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 Number of iterations: 29 CV of field change: 0.000980995 mri_convert ./tmp.mri_nu_correct.mni.3771/nu1.mnc orig_nu.mgz --like orig.mgz --conform mri_convert.bin ./tmp.mri_nu_correct.mni.3771/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.3771/nu1.mnc... TR=0.00, TE=0.00, TI=0.00, flip angle=0.00 i_ras = (-1, -1.28057e-09, 2.32831e-10) j_ras = (-1.16415e-10, 0, -1) k_ras = (-2.38651e-09, 1, -7.45058e-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 Aug 6 14:41:40 -05 2018 mri_nu_correct.mni done \n talairach_avi --i orig_nu.mgz --xfm transforms/talairach.auto.xfm \n talairach_avi log file is transforms/talairach_avi.log... Started at Mon Aug 6 14:41:41 -05 2018 Ended at Mon Aug 6 14:42:19 -05 2018 talairach_avi done \nINFO: transforms/talairach.xfm already exists! The new transforms/talairach.auto.xfm will not be copied to transforms/talairach.xfm This is done to retain any edits made to transforms/talairach.xfm Add the -clean-tal flag to recon-all to overwrite transforms/talairach.xfm\n #-------------------------------------------- #@# Talairach Failure Detection Mon Aug 6 14:42:19 -05 2018 /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri \n talairach_afd -T 0.005 -xfm transforms/talairach.xfm \n talairach_afd: Talairach Transform: transforms/talairach.xfm OK (p=0.6333, pval=0.3663 >= threshold=0.0050) \n awk -f /Applications/freesurfer/bin/extract_talairach_avi_QA.awk /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/transforms/talairach_avi.log \n \n tal_QC_AZS /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/transforms/talairach_avi.log \n TalAviQA: 0.93090 z-score: -10 WARNING: Talairach QA check failed! z-score of -10 is <= threshold of -9\n \nManual Talairach alignment may be necessary, or include the -notal-check flag to skip this test, making sure the -notal-check flag follows -all or -autorecon1 in the command string. See:\n http://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/Talairach INFO: Retrying Talairach align using 3T-based atlas...\n #-------------------------------------------- #@# Talairach Mon Aug 6 14:42:19 -05 2018 /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri \n mri_nu_correct.mni --no-rescale --i orig.mgz --o orig_nu.mgz --n 1 --proto-iters 1000 --distance 50 \n /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri /Applications/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: FreeSurferEnv.csh,v 1.89 2016/06/09 14:54:31 zkaufman Exp $ Darwin Renes-MacBook-Air-2.local 17.5.0 Darwin Kernel Version 17.5.0: Mon Mar 5 22:24:32 PST 2018; root:xnu-4570.51.1~1/RELEASE_X86_64 x86_64 Mon Aug 6 14:42:20 -05 2018 Program nu_correct, built from: Package MNI N3, version 1.12.0, compiled by nicks(a)gust.nmr.mgh.harvard.edu (x86_64-apple-darwin11.4.2) on 2015-06-19 at 15:37:08 /usr/bin/bc tmpdir is ./tmp.mri_nu_correct.mni.5323 /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri mri_convert orig.mgz ./tmp.mri_nu_correct.mni.5323/nu0.mnc -odt float mri_convert.bin orig.mgz ./tmp.mri_nu_correct.mni.5323/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, -1.28057e-09, 2.32831e-10) j_ras = (-1.16415e-10, 0, -1) k_ras = (-2.38651e-09, 1, -7.45058e-09) changing data type from uchar to float (noscale = 0)... writing to ./tmp.mri_nu_correct.mni.5323/nu0.mnc... -------------------------------------------------------- Iteration 1 Mon Aug 6 14:42:25 -05 2018 nu_correct -clobber ./tmp.mri_nu_correct.mni.5323/nu0.mnc ./tmp.mri_nu_correct.mni.5323/nu1.mnc -tmpdir ./tmp.mri_nu_correct.mni.5323/0/ -iterations 1000 -distance 50 [andraderenew@Renes-MacBook-Air-2.local:/Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/] [2018-08-06 14:42:25] running: /Applications/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.5323/0/ ./tmp.mri_nu_correct.mni.5323/nu0.mnc ./tmp.mri_nu_correct.mni.5323/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 Number of iterations: 29 CV of field change: 0.000980995 mri_convert ./tmp.mri_nu_correct.mni.5323/nu1.mnc orig_nu.mgz --like orig.mgz --conform mri_convert.bin ./tmp.mri_nu_correct.mni.5323/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.5323/nu1.mnc... TR=0.00, TE=0.00, TI=0.00, flip angle=0.00 i_ras = (-1, -1.28057e-09, 2.32831e-10) j_ras = (-1.16415e-10, 0, -1) k_ras = (-2.38651e-09, 1, -7.45058e-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 Aug 6 14:43:33 -05 2018 mri_nu_correct.mni done \n talairach_avi --i orig_nu.mgz --xfm transforms/talairach.auto.xfm --atlas 3T18yoSchwartzReactN32_as_orig \n talairach_avi log file is transforms/talairach_avi.log... Started at Mon Aug 6 14:43:34 -05 2018 Ended at Mon Aug 6 14:44:11 -05 2018 talairach_avi done \n cp transforms/talairach.auto.xfm transforms/talairach.xfm \n #-------------------------------------------- #@# Talairach Failure Detection Mon Aug 6 14:44:13 -05 2018 /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri \n talairach_afd -T 0.005 -xfm transforms/talairach.xfm \n talairach_afd: Talairach Transform: transforms/talairach.xfm OK (p=0.3389, pval=0.0406 >= threshold=0.0050) \n awk -f /Applications/freesurfer/bin/extract_talairach_avi_QA.awk /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/transforms/talairach_avi.log \n \n tal_QC_AZS /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/transforms/talairach_avi.log \n TalAviQA: 0.90309 z-score: -17 WARNING: Talairach QA check failed! z-score of -17 is <= threshold of -9\n \nManual Talairach alignment may be necessary, or include the -notal-check flag to skip this test, making sure the -notal-check flag follows -all or -autorecon1 in the command string. See:\n http://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/Talairach INFO: Trying MINC mritotal to perform Talairach align...\n #-------------------------------------------- #@# Talairach Mon Aug 6 14:44:14 -05 2018 /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri \n mri_nu_correct.mni --no-rescale --i orig.mgz --o orig_nu.mgz --n 1 --proto-iters 1000 --distance 50 \n /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri /Applications/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: FreeSurferEnv.csh,v 1.89 2016/06/09 14:54:31 zkaufman Exp $ Darwin Renes-MacBook-Air-2.local 17.5.0 Darwin Kernel Version 17.5.0: Mon Mar 5 22:24:32 PST 2018; root:xnu-4570.51.1~1/RELEASE_X86_64 x86_64 Mon Aug 6 14:44:15 -05 2018 Program nu_correct, built from: Package MNI N3, version 1.12.0, compiled by nicks(a)gust.nmr.mgh.harvard.edu (x86_64-apple-darwin11.4.2) on 2015-06-19 at 15:37:08 /usr/bin/bc tmpdir is ./tmp.mri_nu_correct.mni.6795 /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri mri_convert orig.mgz ./tmp.mri_nu_correct.mni.6795/nu0.mnc -odt float mri_convert.bin orig.mgz ./tmp.mri_nu_correct.mni.6795/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, -1.28057e-09, 2.32831e-10) j_ras = (-1.16415e-10, 0, -1) k_ras = (-2.38651e-09, 1, -7.45058e-09) changing data type from uchar to float (noscale = 0)... writing to ./tmp.mri_nu_correct.mni.6795/nu0.mnc... -------------------------------------------------------- Iteration 1 Mon Aug 6 14:44:22 -05 2018 nu_correct -clobber ./tmp.mri_nu_correct.mni.6795/nu0.mnc ./tmp.mri_nu_correct.mni.6795/nu1.mnc -tmpdir ./tmp.mri_nu_correct.mni.6795/0/ -iterations 1000 -distance 50 [andraderenew@Renes-MacBook-Air-2.local:/Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/] [2018-08-06 14:44:22] running: /Applications/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.6795/0/ ./tmp.mri_nu_correct.mni.6795/nu0.mnc ./tmp.mri_nu_correct.mni.6795/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 Number of iterations: 29 CV of field change: 0.000980995 mri_convert ./tmp.mri_nu_correct.mni.6795/nu1.mnc orig_nu.mgz --like orig.mgz --conform mri_convert.bin ./tmp.mri_nu_correct.mni.6795/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.6795/nu1.mnc... TR=0.00, TE=0.00, TI=0.00, flip angle=0.00 i_ras = (-1, -1.28057e-09, 2.32831e-10) j_ras = (-1.16415e-10, 0, -1) k_ras = (-2.38651e-09, 1, -7.45058e-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 Aug 6 14:45:52 -05 2018 mri_nu_correct.mni done \n talairach --i orig_nu.mgz --xfm transforms/talairach.auto.xfm \n /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri /Applications/freesurfer/bin/talairach --i orig_nu.mgz --xfm transforms/talairach.auto.xfm $Id: FreeSurferEnv.csh,v 1.89 2016/06/09 14:54:31 zkaufman Exp $ Darwin Renes-MacBook-Air-2.local 17.5.0 Darwin Kernel Version 17.5.0: Mon Mar 5 22:24:32 PST 2018; root:xnu-4570.51.1~1/RELEASE_X86_64 x86_64 Mon Aug 6 14:45:52 -05 2018 tmpdir is transforms/tmp.talairach.7685 /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri mri_convert orig_nu.mgz transforms/tmp.talairach.7685/src.mnc mri_convert.bin orig_nu.mgz transforms/tmp.talairach.7685/src.mnc $Id: mri_convert.c,v 1.226 2016/02/26 16:15:24 mreuter Exp $ reading from orig_nu.mgz... TR=0.00, TE=0.00, TI=0.00, flip angle=0.00 i_ras = (-1, -1.28057e-09, 2.32831e-10) j_ras = (-1.16415e-10, 0, -1) k_ras = (-2.38651e-09, 1, -7.45058e-09) writing to transforms/tmp.talairach.7685/src.mnc... -------------------------------------------- mritotal -verbose -debug -clobber -modeldir /Applications/freesurfer/mni/bin/../share/mni_autoreg -protocol icbm transforms/tmp.talairach.7685/src.mnc transforms/talairach.auto.xfm Transforming slices:................................................................................................................................Done Copying chunks:......................................................................................................................................................Done. Copying chunks:..........................................................................................................Done. Transforming slices:......................................................................................................................................................Done Copying chunks:....................................................................................................................Done. Copying chunks:....................................................................................................................Done. Source volume size: 74 by 106 by 106 Source voxel size = 2.000 2.000 2.000 Source min/max real range = -0.000 164.298 Source min/max voxel= -0.000 164.298 Target volume size: 58 by 110 by 86 Target voxel = 2.000 2.000 2.000 Target min/max real range= 0.970 123.710 Target min/max voxel = -0.000 123.710 AFTER init_params() Transform matrix = 1.0000 0.0000 0.0000 1.5580 0.0000 1.0000 0.0000 -25.6781 0.0000 0.0000 1.0000 -8.6102 Transform center = -1.230 8.087 18.065 Transform rotations = 0.000 0.000 0.000 Transform trans = 1.558 -25.678 -8.610 Transform scale = 1.000 1.000 1.000 Transform shear = 0.000 0.000 0.000 Target volume is smallest Lattice step size = 4.000 4.000 4.000 Lattice start = -85.095 -125.510 -47.250 Lattice count = 43 55 29 Source volume size: 84 by 116 by 116 Source voxel size = 2.000 2.000 2.000 Source min/max real range = -0.000 232.183 Source min/max voxel= -0.000 232.183 Target volume size: 68 by 110 by 86 Target voxel = 2.000 2.000 2.000 Target min/max real range= -0.000 144.070 Target min/max voxel = -0.000 144.070 AFTER init_params() Transform matrix = 1.2153 0.2526 0.1517 -3.7258 -0.2847 1.1724 0.3288 -34.3194 -0.0758 -0.3541 1.1969 -9.1699 Transform center = -1.230 8.087 18.065 Transform rotations = -0.288 0.061 -0.230 Transform trans = 0.793 -26.635 -8.383 Transform scale = 1.250 1.250 1.250 Transform shear = -0.000 0.000 0.000 Target volume is smallest Lattice step size = 4.000 4.000 4.000 Lattice start = -85.095 -125.510 -57.250 Lattice count = 43 55 34 Source volume size: 84 by 116 by 116 Source voxel size = 2.000 2.000 2.000 Source min/max real range = 0.109 25.191 Source min/max voxel= 0.109 25.191 Target volume size: 68 by 110 by 86 Target voxel = 2.000 2.000 2.000 Target min/max real range= 0.037 11.652 Target min/max voxel = 0.037 11.652 AFTER init_params() Transform matrix = 1.2114 0.2544 0.2002 -2.5502 -0.3108 1.1309 0.4435 -32.6411 -0.0906 -0.4781 1.1556 -9.7526 Transform center = -1.230 8.087 18.065 Transform rotations = -0.392 0.072 -0.251 Transform trans = 2.865 -23.188 -10.697 Transform scale = 1.254 1.254 1.254 Transform shear = 0.000 -0.000 -0.000 Target volume is smallest Lattice step size = 4.000 4.000 4.000 Lattice start = -65.095 -105.510 -57.250 Lattice count = 35 46 34 Source volume size: 84 by 116 by 116 Source voxel size = 2.000 2.000 2.000 Source min/max real range = 0.109 25.191 Source min/max voxel= 0.109 25.191 Target volume size: 68 by 110 by 86 Target voxel = 2.000 2.000 2.000 Target min/max real range= 0.037 11.652 Target min/max voxel = 0.037 11.652 AFTER init_params() Transform matrix = 1.0541 0.1305 -0.1479 4.6259 -0.1164 1.0608 0.1062 -21.5916 0.1592 -0.0883 1.0568 -15.2192 Transform center = -1.230 8.087 18.065 Transform rotations = -0.083 -0.149 -0.110 Transform trans = 2.943 -19.039 -15.103 Transform scale = 1.072 1.072 1.072 Transform shear = -0.000 0.000 0.000 Target volume is smallest Lattice step size = 4.000 4.000 4.000 Lattice start = -65.095 -105.510 -57.250 Lattice count = 35 46 34 Source volume size: 84 by 116 by 116 Source voxel size = 2.000 2.000 2.000 Source min/max real range = 0.109 25.191 Source min/max voxel= 0.109 25.191 Target volume size: 68 by 110 by 86 Target voxel = 2.000 2.000 2.000 Target min/max real range= 0.037 11.652 Target min/max voxel = 0.037 11.652 AFTER init_params() Transform matrix = 1.0963 0.0565 0.0051 1.5417 -0.0478 0.9255 0.0117 -17.0956 -0.0043 -0.0140 1.0883 -16.0951 Transform center = -1.230 8.087 18.065 Transform rotations = -0.013 0.004 -0.052 Transform trans = 1.972 -17.427 -14.609 Transform scale = 1.098 0.927 1.088 Transform shear = 0.000 0.000 0.000 Target volume is smallest Lattice step size = 4.000 4.000 4.000 Lattice start = -65.095 -105.510 -57.250 Lattice count = 35 46 34 Source volume size: 84 by 116 by 116 Source voxel size = 2.000 2.000 2.000 Source min/max real range = 0.109 25.191 Source min/max voxel= 0.109 25.191 Target volume size: 68 by 110 by 86 Target voxel = 2.000 2.000 2.000 Target min/max real range= 0.037 11.652 Target min/max voxel = 0.037 11.652 AFTER init_params() Transform matrix = 1.0963 0.0565 0.0051 1.5417 -0.0478 0.9255 0.0117 -17.0956 -0.0043 -0.0140 1.0883 -16.0951 Transform center = -1.230 8.087 18.065 Transform rotations = -0.013 0.004 -0.052 Transform trans = 1.972 -17.427 -14.609 Transform scale = 1.098 0.927 1.088 Transform shear = 0.000 -0.000 0.000 Target volume is smallest Lattice step size = 4.000 4.000 4.000 Lattice start = -65.095 -105.510 -57.250 Lattice count = 35 46 34 Mon Aug 6 14:46:09 -05 2018 talairach done \n cp transforms/talairach.auto.xfm transforms/talairach.xfm \n #-------------------------------------------- #@# Talairach Failure Detection Mon Aug 6 14:46:11 -05 2018 /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri \n talairach_afd -T 0.005 -xfm transforms/talairach.xfm \n talairach_afd: Talairach Transform: transforms/talairach.xfm OK (p=0.6333, pval=0.3663 >= threshold=0.0050) #-------------------------------------------- #@# Nu Intensity Correction Mon Aug 6 14:46:11 -05 2018 \n mri_nu_correct.mni --i orig.mgz --o nu.mgz --uchar transforms/talairach.xfm --n 2 \n /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri /Applications/freesurfer/bin/mri_nu_correct.mni --i orig.mgz --o nu.mgz --uchar transforms/talairach.xfm --n 2 nIters 2 $Id: FreeSurferEnv.csh,v 1.89 2016/06/09 14:54:31 zkaufman Exp $ Darwin Renes-MacBook-Air-2.local 17.5.0 Darwin Kernel Version 17.5.0: Mon Mar 5 22:24:32 PST 2018; root:xnu-4570.51.1~1/RELEASE_X86_64 x86_64 Mon Aug 6 14:46:12 -05 2018 Program nu_correct, built from: Package MNI N3, version 1.12.0, compiled by nicks(a)gust.nmr.mgh.harvard.edu (x86_64-apple-darwin11.4.2) on 2015-06-19 at 15:37:08 /usr/bin/bc tmpdir is ./tmp.mri_nu_correct.mni.8095 /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri mri_convert orig.mgz ./tmp.mri_nu_correct.mni.8095/nu0.mnc -odt float mri_convert.bin orig.mgz ./tmp.mri_nu_correct.mni.8095/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, -1.28057e-09, 2.32831e-10) j_ras = (-1.16415e-10, 0, -1) k_ras = (-2.38651e-09, 1, -7.45058e-09) changing data type from uchar to float (noscale = 0)... writing to ./tmp.mri_nu_correct.mni.8095/nu0.mnc... -------------------------------------------------------- Iteration 1 Mon Aug 6 14:46:19 -05 2018 nu_correct -clobber ./tmp.mri_nu_correct.mni.8095/nu0.mnc ./tmp.mri_nu_correct.mni.8095/nu1.mnc -tmpdir ./tmp.mri_nu_correct.mni.8095/0/ [andraderenew@Renes-MacBook-Air-2.local:/Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/] [2018-08-06 14:46:19] running: /Applications/freesurfer/mni/bin/nu_estimate_np_and_em -parzen -log -sharpen 0.15 0.01 -iterations 50 -stop 0.001 -shrink 4 -auto_mask -nonotify -b_spline 1.0e-7 -distance 200 -quiet -execute -clobber -nokeeptmp -tmpdir ./tmp.mri_nu_correct.mni.8095/0/ ./tmp.mri_nu_correct.mni.8095/nu0.mnc ./tmp.mri_nu_correct.mni.8095/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 Number of iterations: 19 CV of field change: 0.000946982 -------------------------------------------------------- Iteration 2 Mon Aug 6 14:47:27 -05 2018 nu_correct -clobber ./tmp.mri_nu_correct.mni.8095/nu1.mnc ./tmp.mri_nu_correct.mni.8095/nu2.mnc -tmpdir ./tmp.mri_nu_correct.mni.8095/1/ [andraderenew@Renes-MacBook-Air-2.local:/Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/] [2018-08-06 14:47:27] running: /Applications/freesurfer/mni/bin/nu_estimate_np_and_em -parzen -log -sharpen 0.15 0.01 -iterations 50 -stop 0.001 -shrink 4 -auto_mask -nonotify -b_spline 1.0e-7 -distance 200 -quiet -execute -clobber -nokeeptmp -tmpdir ./tmp.mri_nu_correct.mni.8095/1/ ./tmp.mri_nu_correct.mni.8095/nu1.mnc ./tmp.mri_nu_correct.mni.8095/nu2.imp Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Processing:.................................................................Done Number of iterations: 10 CV of field change: 0.00095123 mri_binarize --i ./tmp.mri_nu_correct.mni.8095/nu2.mnc --min -1 --o ./tmp.mri_nu_correct.mni.8095/ones.mgz $Id: mri_binarize.c,v 1.43 2016/06/09 20:46:21 greve Exp $ cwd /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri cmdline mri_binarize.bin --i ./tmp.mri_nu_correct.mni.8095/nu2.mnc --min -1 --o ./tmp.mri_nu_correct.mni.8095/ones.mgz sysname Darwin hostname Renes-MacBook-Air-2.local machine x86_64 user andraderenew input ./tmp.mri_nu_correct.mni.8095/nu2.mnc frame 0 nErode3d 0 nErode2d 0 output ./tmp.mri_nu_correct.mni.8095/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.8095/ones.mgz --i orig.mgz --sum ./tmp.mri_nu_correct.mni.8095/sum.junk --avgwf ./tmp.mri_nu_correct.mni.8095/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.8095/ones.mgz --i orig.mgz --sum ./tmp.mri_nu_correct.mni.8095/sum.junk --avgwf ./tmp.mri_nu_correct.mni.8095/input.mean.dat sysname Darwin hostname Renes-MacBook-Air-2.local machine x86_64 user andraderenew UseRobust 0 Loading ./tmp.mri_nu_correct.mni.8095/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.8095/input.mean.dat mri_segstats done mri_segstats --id 1 --seg ./tmp.mri_nu_correct.mni.8095/ones.mgz --i ./tmp.mri_nu_correct.mni.8095/nu2.mnc --sum ./tmp.mri_nu_correct.mni.8095/sum.junk --avgwf ./tmp.mri_nu_correct.mni.8095/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.8095/ones.mgz --i ./tmp.mri_nu_correct.mni.8095/nu2.mnc --sum ./tmp.mri_nu_correct.mni.8095/sum.junk --avgwf ./tmp.mri_nu_correct.mni.8095/output.mean.dat sysname Darwin hostname Renes-MacBook-Air-2.local machine x86_64 user andraderenew UseRobust 0 Loading ./tmp.mri_nu_correct.mni.8095/ones.mgz Loading ./tmp.mri_nu_correct.mni.8095/nu2.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.8095/output.mean.dat mri_segstats done mris_calc -o ./tmp.mri_nu_correct.mni.8095/nu2.mnc ./tmp.mri_nu_correct.mni.8095/nu2.mnc mul 1.00543850331096404690 Saving result to './tmp.mri_nu_correct.mni.8095/nu2.mnc' (type = MINC ) [ ok ] mri_convert ./tmp.mri_nu_correct.mni.8095/nu2.mnc nu.mgz --like orig.mgz mri_convert.bin ./tmp.mri_nu_correct.mni.8095/nu2.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.8095/nu2.mnc... TR=0.00, TE=0.00, TI=0.00, flip angle=0.00 i_ras = (-1, -1.28057e-09, 2.32831e-10) j_ras = (-1.16415e-10, 0, -1) k_ras = (-2.38651e-09, 1, -7.45058e-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 ( 5, 147) to ( 3, 110) Mon Aug 6 14:48:57 -05 2018 mri_nu_correct.mni done \n mri_add_xform_to_header -c /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/transforms/talairach.xfm nu.mgz nu.mgz \n INFO: extension is mgz #-------------------------------------------- #@# Intensity Normalization Mon Aug 6 14:48:59 -05 2018 /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri \n mri_normalize -g 1 -mprage nu.mgz T1.mgz \n using max gradient = 1.000 assuming input volume is MGH (Van der Kouwe) MP-RAGE reading from nu.mgz... normalizing image... talairach transform 1.09627 0.05654 0.00505 1.54172; -0.04779 0.92548 0.01174 -17.09556; -0.00429 -0.01403 1.08825 -16.09510; 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 = 14 Starting OpenSpline(): npoints = 14 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 77 (77), valley at 0 (-1) csf peak at 38, setting threshold to 64 building Voronoi diagram... performing soap bubble smoothing, sigma = 8... --------------------------------- 3d normalization pass 2 of 2 white matter peak found at 110 white matter peak found at 110 gm peak at 77 (77), valley at 0 (-1) csf peak at 38, setting threshold to 64 building Voronoi diagram... performing soap bubble smoothing, sigma = 8... Done iterating --------------------------------- writing output to T1.mgz 3D bias adjustment took 2 minutes and 41 seconds. #-------------------------------------------- #@# Skull Stripping Mon Aug 6 14:51:42 -05 2018 /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri \n mri_watershed -rusage /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/touch/rusage.mri_watershed.dat -keep brainmask.auto.mgz brainmask.mgz brainmask.mgz -T1 -brain_atlas /Applications/freesurfer/average/RB_all_withskull_2016-05-10.vc700.gca transforms/talairach_with_skull.lta T1.mgz brainmask.auto.mgz \n Keeping brain edits brainmask.auto.mgz brainmask.mgz Mode: T1 normalized volume Mode: Use the information of atlas (default parms, --help for details) ********************************************************* The input file is T1.mgz The output file is brainmask.auto.mgz Weighting the input with atlas information before watershed *************************WATERSHED************************** Sorting... first estimation of the COG coord: x=118 y=133 z=111 r=64 first estimation of the main basin volume: 1111304 voxels Looking for seedpoints 2 found in the cerebellum 5 found in the rest of the brain global maximum in x=114, y=127, z=109, Imax=255 CSF=23, 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=983172784576193 voxels, voxel volume =1.000 = 983172784576193 mmm3 = 983172774887.424 cm3 done. PostAnalyze...Basin Prior 37 basins merged thanks to atlas ambiguous basin, merged: at least 49 ambiguous voxels; size: 116744 voxels ***** 1 basin(s) merged in 2 iteration(s) ***** 116744 voxel(s) added to the main basin ambiguous basin, non merged: 12 ambiguous voxels; size: 20473 voxels ambiguous basin, non merged: 4 ambiguous voxels; size: 2912 voxels done. Weighting the input with prior template ****************TEMPLATE DEFORMATION**************** second estimation of the COG coord: x=119,y=142, z=113, r=10387 iterations ^^^^^^^^ couldn't find WM with original limits - expanding ^^^^^^ GLOBAL CSF_MIN=1, CSF_intensity=2, CSF_MAX=42 , nb = 18582 RIGHT_CER CSF_MIN=1, CSF_intensity=2, CSF_MAX=31 , nb = 1086310830 LEFT_CER CSF_MIN=1, CSF_intensity=2, CSF_MAX=16 , nb = -1069450356 RIGHT_BRAIN CSF_MIN=1, CSF_intensity=2, CSF_MAX=34 , nb = -1037928638 LEFT_BRAIN CSF_MIN=0, CSF_intensity=6, CSF_MAX=20 , nb = 547 OTHER CSF_MIN=1, CSF_intensity=2, CSF_MAX=50 , nb = 1086332314 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 : 42, 77, 84, 91 after analyzing : 42, 81, 84, 83 RIGHT_CER before analyzing : 31, 70, 83, 92 after analyzing : 31, 78, 83, 81 LEFT_CER before analyzing : 16, 56, 83, 92 after analyzing : 16, 74, 83, 78 RIGHT_BRAIN before analyzing : 34, 62, 76, 92 after analyzing : 34, 71, 76, 76 LEFT_BRAIN before analyzing : 20, 62, 84, 91 after analyzing : 20, 76, 84, 79 OTHER before analyzing : 50, 76, 82, 91 after analyzing : 50, 80, 82, 82 mri_strip_skull: done peeling brain highly tesselated surface with 10242 vertices matching...63 iterations *********************VALIDATION********************* curvature mean = -0.017, std = 0.017 curvature mean = 53.554, std = 8.717 No Rigid alignment: -atlas Mode Off (basic atlas / no registration) before rotation: sse = 10.61, sigma = 20.74 after rotation: sse = 10.61, sigma = 20.74 Localization of inacurate regions: Erosion-Dilation steps the sse mean is 15.56, its var is 26.10 before Erosion-Dilatation 17.22% of inacurate vertices after Erosion-Dilatation 27.66% of inacurate vertices 46.17% of 'positive' inacurate vertices 53.83% of 'negative' inacurate vertices The surface validation has detected a possible Error If the final segmentation is not valid, try using the option '-atlas' Scaling of atlas fields onto current surface fields ********FINAL ITERATIVE TEMPLATE DEFORMATION******** Compute Local values csf/gray Fine Segmentation...43 iterations mri_strip_skull: done peeling brain Brain Size = 622091 voxels, voxel volume = 1.000 mm3 = 622091 mmm3 = 622.091 cm3 ****************************** Saving brainmask.auto.mgz Keeping edits ... Saving kept edits to brainmask.mgz ..... done mri_watershed utimesec 36.072640 mri_watershed stimesec 0.673701 mri_watershed ru_maxrss 729980928 mri_watershed ru_ixrss 0 mri_watershed ru_idrss 0 mri_watershed ru_isrss 0 mri_watershed ru_minflt 199651 mri_watershed ru_majflt 249 mri_watershed ru_nswap 0 mri_watershed ru_inblock 0 mri_watershed ru_oublock 12 mri_watershed ru_msgsnd 0 mri_watershed ru_msgrcv 0 mri_watershed ru_nsignals 0 mri_watershed ru_nvcsw 34 mri_watershed ru_nivcsw 40895 mri_watershed done \nINFO: brainmask.mgz already exists! The new brainmask.auto.mgz will not be copied to brainmask.mgz. This is done to retain any edits made to brainmask.mgz. Add the -clean-bm flag to recon-all to overwrite brainmask.mgz.\n #------------------------------------- #@# EM Registration Mon Aug 6 14:52:20 -05 2018 /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri \n mri_em_register -rusage /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/touch/rusage.mri_em_register.dat -uns 3 -mask brainmask.mgz nu.mgz /Applications/freesurfer/average/RB_all_2016-05-10.vc700.gca transforms/talairach.lta \n 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 '/Applications/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=35.0 skull bounding box = (80, 105, 46) --> (162, 168, 161) using (107, 126, 104) as brain centroid... mean wm in atlas = 107, using box (97,118,90) --> (116, 133,118) to find MRI wm before smoothing, mri peak at 51 robust fit to distribution - 54 +- 5.8 distribution too broad for accurate scaling - disabling after smoothing, mri peak at 107, scaling input intensities by 1.000 scaling channel 0 by 1 initial log_p = -4.624 ************************************************ First Search limited to translation only. ************************************************ max log p = -4.536795 @ (9.091, 9.091, -9.091) max log p = -4.494132 @ (-4.545, 4.545, 4.545) max log p = -4.491376 @ (-2.273, -2.273, -2.273) max log p = -4.478565 @ (1.136, 3.409, 1.136) max log p = -4.463528 @ (0.568, -1.705, -1.705) max log p = -4.463528 @ (0.000, 0.000, 0.000) Found translation: (4.0, 13.1, -7.4): log p = -4.464 **************************************** Nine parameter search. iteration 0 nscales = 0 ... **************************************** Result so far: scale 1.000: max_log_p=-4.458, old_max_log_p =-4.464 (thresh=-4.5) 1.06580 0.01831 0.13912 -21.74265; 0.00000 0.91709 -0.12074 35.49821; -0.12074 0.11970 0.90924 -2.53948; 0.00000 0.00000 0.00000 1.00000; **************************************** Nine parameter search. iteration 1 nscales = 0 ... **************************************** Result so far: scale 1.000: max_log_p=-4.458, old_max_log_p =-4.458 (thresh=-4.5) 1.15288 0.00272 0.02069 -16.36129; 0.00000 0.84831 -0.11168 49.28259; 0.01796 0.11199 0.85065 -11.51312; 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=-4.430, old_max_log_p =-4.458 (thresh=-4.5) 1.20401 0.13142 0.09435 -47.94740; -0.14950 0.83879 -0.12790 66.64242; -0.09582 0.11711 0.85998 -1.37744; 0.00000 0.00000 0.00000 1.00000; **************************************** Nine parameter search. iteration 3 nscales = 1 ... **************************************** Result so far: scale 0.250: max_log_p=-4.430, old_max_log_p =-4.430 (thresh=-4.4) 1.20401 0.13142 0.09435 -47.94740; -0.14950 0.83879 -0.12790 66.64242; -0.09582 0.11711 0.85998 -1.37744; 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=-4.425, old_max_log_p =-4.430 (thresh=-4.4) 1.20802 0.12486 0.09562 -47.45150; -0.13978 0.84082 -0.12727 65.14833; -0.09571 0.11698 0.85897 -1.25226; 0.00000 0.00000 0.00000 1.00000; **************************************** Nine parameter search. iteration 5 nscales = 2 ... **************************************** Result so far: scale 0.062: max_log_p=-4.425, old_max_log_p =-4.425 (thresh=-4.4) 1.20802 0.12486 0.09562 -47.45150; -0.13978 0.84082 -0.12727 65.14833; -0.09571 0.11698 0.85897 -1.25226; 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 1.20802 0.12486 0.09562 -47.45150; -0.13978 0.84082 -0.12727 65.14833; -0.09571 0.11698 0.85897 -1.25226; 0.00000 0.00000 0.00000 1.00000; nsamples 2830 Quasinewton: input matrix 1.20802 0.12486 0.09562 -47.45150; -0.13978 0.84082 -0.12727 65.14833; -0.09571 0.11698 0.85897 -1.25226; 0.00000 0.00000 0.00000 1.00000; IFLAG= -1 LINE SEARCH FAILED. SEE DOCUMENTATION OF ROUTINE MCSRCH ERROR RETURN OF LINE SEARCH: INFO= 3 POSSIBLE CAUSES: FUNCTION OR GRADIENT ARE INCORRECT OR INCORRECT TOLERANCESoutof QuasiNewtonEMA: 008: -log(p) = -0.0 tol 0.000010 Resulting transform: 1.20802 0.12486 0.09562 -47.45150; -0.13978 0.84082 -0.12727 65.14833; -0.09571 0.11698 0.85897 -1.25226; 0.00000 0.00000 0.00000 1.00000; pass 1, spacing 8: log(p) = -4.425 (old=-4.624) transform before final EM align: 1.20802 0.12486 0.09562 -47.45150; -0.13978 0.84082 -0.12727 65.14833; -0.09571 0.11698 0.85897 -1.25226; 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 1.20802 0.12486 0.09562 -47.45150; -0.13978 0.84082 -0.12727 65.14833; -0.09571 0.11698 0.85897 -1.25226; 0.00000 0.00000 0.00000 1.00000; nsamples 315557 Quasinewton: input matrix 1.20802 0.12486 0.09562 -47.45150; -0.13978 0.84082 -0.12727 65.14833; -0.09571 0.11698 0.85897 -1.25226; 0.00000 0.00000 0.00000 1.00000; IFLAG= -1 LINE SEARCH FAILED. SEE DOCUMENTATION OF ROUTINE MCSRCH ERROR RETURN OF LINE SEARCH: INFO= 6 POSSIBLE CAUSES: FUNCTION OR GRADIENT ARE INCORRECT OR INCORRECT TOLERANCESoutof QuasiNewtonEMA: 010: -log(p) = 4.7 tol 0.000000 final transform: 1.20802 0.12486 0.09562 -47.45150; -0.13978 0.84082 -0.12727 65.14833; -0.09571 0.11698 0.85897 -1.25226; 0.00000 0.00000 0.00000 1.00000; writing output transformation to transforms/talairach.lta... mri_em_register utimesec 917.554305 mri_em_register stimesec 3.622811 mri_em_register ru_maxrss 482205696 mri_em_register ru_ixrss 0 mri_em_register ru_idrss 0 mri_em_register ru_isrss 0 mri_em_register ru_minflt 124695 mri_em_register ru_majflt 208 mri_em_register ru_nswap 0 mri_em_register ru_inblock 2 mri_em_register ru_oublock 6 mri_em_register ru_msgsnd 0 mri_em_register ru_msgrcv 0 mri_em_register ru_nsignals 0 mri_em_register ru_nvcsw 15 mri_em_register ru_nivcsw 442694 registration took 15 minutes and 36 seconds. #-------------------------------------- #@# CA Normalize Mon Aug 6 15:07:56 -05 2018 /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri \n mri_ca_normalize -c ctrl_pts.mgz -mask brainmask.mgz nu.mgz /Applications/freesurfer/average/RB_all_2016-05-10.vc700.gca transforms/talairach.lta norm.mgz \n writing control point volume to ctrl_pts.mgz using MR volume brainmask.mgz to mask input volume... reading 1 input volume reading atlas from '/Applications/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=35.0 skull bounding box = (79, 105, 46) --> (162, 168, 161) using (107, 126, 104) as brain centroid... mean wm in atlas = 107, using box (97,118,90) --> (117, 133,118) to find MRI wm before smoothing, mri peak at 51 robust fit to distribution - 54 +- 5.4 distribution too broad for accurate scaling - disabling after smoothing, mri peak at 107, scaling input intensities by 1.000 scaling channel 0 by 1 using 246344 sample points... INFO: compute sample coordinates transform 1.20802 0.12486 0.09562 -47.45150; -0.13978 0.84082 -0.12727 65.14833; -0.09571 0.11698 0.85897 -1.25226; 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 (117, 26, 31) --> (179, 172, 225) Left_Cerebral_White_Matter: limiting intensities to 88.0 --> 132.0 12 of 12 (100.0%) samples deleted finding control points in Right_Cerebral_White_Matter.... found 39557 control points for structure... bounding box (69, 22, 32) --> (130, 164, 224) Right_Cerebral_White_Matter: limiting intensities to 88.0 --> 132.0 20 of 20 (100.0%) samples deleted finding control points in Left_Cerebellum_White_Matter.... found 3059 control points for structure... bounding box (124, 120, 51) --> (162, 174, 115) Left_Cerebellum_White_Matter: limiting intensities to 88.0 --> 132.0 16 of 16 (100.0%) samples deleted finding control points in Right_Cerebellum_White_Matter.... found 2705 control points for structure... bounding box (85, 120, 48) --> (125, 167, 114) Right_Cerebellum_White_Matter: limiting intensities to 88.0 --> 132.0 22 of 22 (100.0%) samples deleted finding control points in Brain_Stem.... found 3518 control points for structure... bounding box (105, 114, 86) --> (135, 194, 128) Brain_Stem: limiting intensities to 88.0 --> 132.0 7 of 7 (100.0%) samples deleted using 77 total control points for intensity normalization... 0 of 0 control points discarded finding control points in Left_Cerebral_White_Matter.... found 39915 control points for structure... bounding box (117, 26, 31) --> (179, 172, 225) finding control points in Right_Cerebral_White_Matter.... found 39557 control points for structure... bounding box (69, 22, 32) --> (130, 164, 224) finding control points in Left_Cerebellum_White_Matter.... found 3059 control points for structure... bounding box (124, 120, 51) --> (162, 174, 115) finding control points in Right_Cerebellum_White_Matter.... found 2705 control points for structure... bounding box (85, 120, 48) --> (125, 167, 114) finding control points in Brain_Stem.... found 3518 control points for structure... bounding box (105, 114, 86) --> (135, 194, 128) skipping region 2 with no control points detected finding control points in Left_Cerebral_White_Matter.... found 39915 control points for structure... bounding box (117, 26, 31) --> (179, 172, 225) finding control points in Right_Cerebral_White_Matter.... found 39557 control points for structure... bounding box (69, 22, 32) --> (130, 164, 224) finding control points in Left_Cerebellum_White_Matter.... found 3059 control points for structure... bounding box (124, 120, 51) --> (162, 174, 115) finding control points in Right_Cerebellum_White_Matter.... found 2705 control points for structure... bounding box (85, 120, 48) --> (125, 167, 114) finding control points in Brain_Stem.... found 3518 control points for structure... bounding box (105, 114, 86) --> (135, 194, 128) skipping region 3 with no control points detected writing normalized volume to norm.mgz... writing control points to ctrl_pts.mgz freeing GCA...done. normalization took 0 minutes and 42 seconds. #-------------------------------------- #@# CA Reg Mon Aug 6 15:08:38 -05 2018 /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri \n mri_ca_register -rusage /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/touch/rusage.mri_ca_register.dat -nobigventricles -T transforms/talairach.lta -align-after -mask brainmask.mgz norm.mgz /Applications/freesurfer/average/RB_all_2016-05-10.vc700.gca transforms/talairach.m3z \n 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 '/Applications/freesurfer/average/RB_all_2016-05-10.vc700.gca'... label assignment complete, 0 changed (0.00%) det(m_affine) = 0.91 (predicted orig area = 8.8) 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=2.181, neg=0, invalid=762 0001: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0002: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0003: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0004: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 setting smoothness coefficient to 0.154 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0005: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0006: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0007: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0008: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 setting smoothness coefficient to 0.588 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0009: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0010: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0011: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0012: dt=0.000000, rms=2.177 (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=2.181, neg=0, invalid=762 0013: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0014: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0015: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0016: dt=0.000000, rms=2.177 (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=2.181, neg=0, invalid=762 0017: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0018: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0019: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0020: dt=0.000000, rms=2.177 (0.000%), 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=2.181, neg=0, invalid=762 0021: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0022: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0023: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0024: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 renormalizing by structure alignment.... renormalizing input #0 gca peak = 0.10027 (20) gca peak = 0.15565 (16) gca peak = 0.26829 (96) gca peak = 0.20183 (93) gca peak = 0.21683 (55) gca peak = 0.30730 (58) gca peak = 0.11430 (101) gca peak = 0.12076 (102) gca peak = 0.14995 (59) gca peak = 0.15082 (58) gca peak = 0.14161 (67) gca peak = 0.15243 (71) gca peak = 0.13336 (57) gca peak = 0.13252 (56) gca peak = 0.18181 (84) gca peak = 0.20573 (83) gca peak = 0.21969 (57) gca peak = 0.39313 (56) gca peak = 0.14181 (85) gca peak = 0.11978 (83) gca peak = 0.13399 (79) gca peak = 0.14159 (79) gca peak = 0.10025 (80) gca peak = 0.13281 (86) gca peak = 0.12801 (89) gca peak = 0.20494 (23) gca peak = 0.15061 (21) gca peak Unknown = 0.94835 ( 0) gca peak Left_Cerebral_White_Matter = 0.12076 (102) gca peak Left_Cerebral_Cortex = 0.14995 (59) gca peak Left_Lateral_Ventricle = 0.10027 (20) gca peak Left_Inf_Lat_Vent = 0.18056 (32) gca peak Left_Cerebellum_White_Matter = 0.18181 (84) gca peak Left_Cerebellum_Cortex = 0.13336 (57) gca peak Left_Thalamus = 0.64095 (94) gca peak Left_Thalamus_Proper = 0.14181 (85) gca peak Left_Caudate = 0.15243 (71) gca peak Left_Putamen = 0.13399 (79) gca peak Left_Pallidum = 0.20183 (93) gca peak Third_Ventricle = 0.20494 (23) gca peak Fourth_Ventricle = 0.15061 (21) gca peak Brain_Stem = 0.10025 (80) gca peak Left_Hippocampus = 0.30730 (58) gca peak Left_Amygdala = 0.21969 (57) gca peak CSF = 0.20999 (34) gca peak Left_Accumbens_area = 0.39030 (62) gca peak Left_VentralDC = 0.12801 (89) 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_Cerebral_White_Matter = 0.11430 (101) gca peak Right_Cerebral_Cortex = 0.15082 (58) gca peak Right_Lateral_Ventricle = 0.15565 (16) gca peak Right_Inf_Lat_Vent = 0.23544 (26) gca peak Right_Cerebellum_White_Matter = 0.20573 (83) gca peak Right_Cerebellum_Cortex = 0.13252 (56) gca peak Right_Thalamus_Proper = 0.11978 (83) gca peak Right_Caudate = 0.14161 (67) gca peak Right_Putamen = 0.14159 (79) gca peak Right_Pallidum = 0.26829 (96) gca peak Right_Hippocampus = 0.21683 (55) gca peak Right_Amygdala = 0.39313 (56) gca peak Right_Accumbens_area = 0.30312 (64) gca peak Right_VentralDC = 0.13281 (86) 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 1.00 x + 0.0 estimating mean wm scale to be 1.00 x + 0.0 estimating mean csf scale to be 1.00 x + 0.0 setting left cbm cortex = 1.00 x + 0.00 setting right cbm cortex = 1.00 x + 0.00 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=2.181, neg=0, invalid=762 0025: dt=0.005645, rms=2.177 (0.184%), neg=0, invalid=762 0026: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 0027: dt=0.850000, rms=2.177 (-0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0028: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0029: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 0030: dt=0.850000, rms=2.177 (-0.000%), neg=0, invalid=762 setting smoothness coefficient to 0.031 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0031: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0032: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 0033: dt=0.450000, rms=2.177 (-0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0034: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0035: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 0036: dt=0.450000, rms=2.177 (-0.000%), neg=0, invalid=762 setting smoothness coefficient to 0.118 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0037: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0038: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 0039: dt=0.250000, rms=2.177 (-0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0040: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0041: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 0042: dt=0.250000, rms=2.177 (-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=2.181, neg=0, invalid=762 0043: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0044: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 0045: dt=0.150000, rms=2.177 (-0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0046: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0047: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 0048: dt=0.150000, rms=2.177 (-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=2.181, neg=0, invalid=762 0049: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0050: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 0051: dt=0.100000, rms=2.177 (-0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0052: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0053: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 0054: dt=0.100000, rms=2.177 (-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=2.181, neg=0, invalid=762 0055: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0056: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 0057: dt=0.050000, rms=2.177 (-0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0058: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0059: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 0060: dt=0.050000, rms=2.177 (-0.000%), 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=2.181, neg=0, invalid=762 0061: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0062: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0063: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0064: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 setting smoothness coefficient to 0.031 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0065: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0066: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0067: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0068: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 setting smoothness coefficient to 0.118 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0069: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0070: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0071: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0072: dt=0.000000, rms=2.177 (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=2.181, neg=0, invalid=762 0073: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0074: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0075: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0076: dt=0.000000, rms=2.177 (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=2.181, neg=0, invalid=762 0077: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0078: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0079: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0080: dt=0.000000, rms=2.177 (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=2.181, neg=0, invalid=762 0081: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0082: dt=0.000000, rms=2.177 (0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0083: dt=0.000000, rms=2.177 (0.184%), neg=0, invalid=762 0084: dt=0.000000, rms=2.177 (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=2.181, neg=0, invalid=762 0085: dt=4734.976000, rms=2.181 (0.000%), neg=0, invalid=762 0086: dt=4734.976000, rms=2.181 (-0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0087: dt=0.000000, rms=2.181 (0.000%), neg=0, invalid=762 setting smoothness coefficient to 0.031 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0088: dt=0.000000, rms=2.181 (0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0089: dt=0.000000, rms=2.181 (0.000%), neg=0, invalid=762 setting smoothness coefficient to 0.118 blurring input image with Gaussian with sigma=2.000... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0090: dt=716.800000, rms=2.181 (0.000%), neg=0, invalid=762 0091: dt=716.800000, rms=2.181 (0.000%), neg=0, invalid=762 0092: dt=716.800000, rms=2.181 (0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0093: dt=0.000000, rms=2.181 (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=2.181, neg=0, invalid=762 0094: dt=46.080000, rms=2.181 (0.000%), neg=0, invalid=762 0095: dt=46.080000, rms=2.181 (0.000%), neg=0, invalid=762 0096: dt=46.080000, rms=2.181 (0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0097: dt=46.080000, rms=2.181 (0.000%), neg=0, invalid=762 0098: dt=46.080000, rms=2.181 (0.000%), neg=0, invalid=762 0099: dt=46.080000, rms=2.181 (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=2.181, neg=0, invalid=762 0100: dt=6.144000, rms=2.181 (0.000%), neg=0, invalid=762 0101: dt=6.144000, rms=2.181 (0.000%), neg=0, invalid=762 0102: dt=6.144000, rms=2.181 (0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0103: dt=6.144000, rms=2.181 (0.000%), neg=0, invalid=762 0104: dt=6.144000, rms=2.181 (0.000%), neg=0, invalid=762 0105: dt=6.144000, rms=2.181 (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=2.181, neg=0, invalid=762 0106: dt=0.000000, rms=2.181 (0.000%), neg=0, invalid=762 blurring input image with Gaussian with sigma=0.500... 0000: dt=0.000, rms=2.181, neg=0, invalid=762 0107: dt=0.000000, rms=2.181 (0.000%), neg=0, invalid=762 writing output transformation to transforms/talairach.m3z... GCAMwrite mri_ca_register took 1 hours, 15 minutes and 45 seconds. mri_ca_register utimesec 4292.110272 mri_ca_register stimesec 30.339200 mri_ca_register ru_maxrss 1274769408 mri_ca_register ru_ixrss 0 mri_ca_register ru_idrss 0 mri_ca_register ru_isrss 0 mri_ca_register ru_minflt 761256 mri_ca_register ru_majflt 251 mri_ca_register ru_nswap 0 mri_ca_register ru_inblock 2 mri_ca_register ru_oublock 7 mri_ca_register ru_msgsnd 0 mri_ca_register ru_msgrcv 0 mri_ca_register ru_nsignals 0 mri_ca_register ru_nvcsw 16 mri_ca_register ru_nivcsw 4259738 FSRUNTIME@ mri_ca_register 1.2625 hours 1 threads #-------------------------------------- #@# SubCort Seg Mon Aug 6 16:24:24 -05 2018 \n mri_ca_label -relabel_unlikely 9 .3 -prior 0.5 -align norm.mgz transforms/talairach.m3z /Applications/freesurfer/average/RB_all_2016-05-10.vc700.gca aseg.auto_noCCseg.mgz \n sysname Darwin hostname Renes-MacBook-Air-2.local machine x86_64 setenv SUBJECTS_DIR /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir cd /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri mri_ca_label -relabel_unlikely 9 .3 -prior 0.5 -align norm.mgz transforms/talairach.m3z /Applications/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 /Applications/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 8.76 Atlas used for the 3D morph was /Applications/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) gca peak = 0.17677 (13) gca peak = 0.28129 (95) gca peak = 0.16930 (96) gca peak = 0.24553 (55) gca peak = 0.30264 (59) gca peak = 0.07580 (103) gca peak = 0.07714 (104) gca peak = 0.09712 (58) gca peak = 0.11620 (58) gca peak = 0.30970 (66) gca peak = 0.15280 (69) gca peak = 0.13902 (56) gca peak = 0.14777 (55) gca peak = 0.16765 (84) gca peak = 0.18739 (84) gca peak = 0.29869 (57) gca peak = 0.33601 (57) gca peak = 0.11131 (90) gca peak = 0.11793 (83) gca peak = 0.08324 (81) gca peak = 0.10360 (77) gca peak = 0.08424 (78) gca peak = 0.12631 (89) gca peak = 0.14500 (87) gca peak = 0.14975 (24) gca peak = 0.19357 (14) gca peak Unknown = 0.94835 ( 0) gca peak Left_Cerebral_White_Matter = 0.07714 (104) gca peak Left_Cerebral_Cortex = 0.09712 (58) gca peak Left_Lateral_Ventricle = 0.16259 (20) gca peak Left_Inf_Lat_Vent = 0.16825 (27) gca peak Left_Cerebellum_White_Matter = 0.16765 (84) gca peak Left_Cerebellum_Cortex = 0.13902 (56) gca peak Left_Thalamus = 1.00000 (94) gca peak Left_Thalamus_Proper = 0.11131 (90) gca peak Left_Caudate = 0.15280 (69) gca peak Left_Putamen = 0.08324 (81) gca peak Left_Pallidum = 0.16930 (96) gca peak Third_Ventricle = 0.14975 (24) gca peak Fourth_Ventricle = 0.19357 (14) gca peak Brain_Stem = 0.08424 (78) gca peak Left_Hippocampus = 0.30264 (59) gca peak Left_Amygdala = 0.29869 (57) gca peak CSF = 0.23379 (36) gca peak Left_Accumbens_area = 0.70037 (62) gca peak Left_VentralDC = 0.14500 (87) 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_Cerebral_White_Matter = 0.07580 (103) gca peak Right_Cerebral_Cortex = 0.11620 (58) gca peak Right_Lateral_Ventricle = 0.17677 (13) gca peak Right_Inf_Lat_Vent = 0.24655 (23) gca peak Right_Cerebellum_White_Matter = 0.18739 (84) gca peak Right_Cerebellum_Cortex = 0.14777 (55) gca peak Right_Thalamus_Proper = 0.11793 (83) gca peak Right_Caudate = 0.30970 (66) gca peak Right_Putamen = 0.10360 (77) gca peak Right_Pallidum = 0.28129 (95) gca peak Right_Hippocampus = 0.24553 (55) gca peak Right_Amygdala = 0.33601 (57) gca peak Right_Accumbens_area = 0.45042 (65) gca peak Right_VentralDC = 0.12631 (89) 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 1.00 x + 0.0 estimating mean wm scale to be 1.00 x + 0.0 estimating mean csf scale to be 1.00 x + 0.0 setting left cbm cortex = 1.00 x + 0.00 setting right cbm cortex = 1.00 x + 0.00 saving intensity scales to aseg.auto_noCCseg.label_intensities.txt renormalizing by structure alignment.... renormalizing input #0 gca peak = 0.16259 (20) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.17677 (13) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.28129 (95) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.16930 (96) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.24553 (55) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.30264 (59) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.07580 (103) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.07714 (104) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.09712 (58) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.11620 (58) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.30970 (66) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.15280 (69) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.13902 (56) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.14777 (55) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.16765 (84) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.18739 (84) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.29869 (57) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.33601 (57) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.11131 (90) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.11793 (83) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.08324 (81) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.10360 (77) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.08424 (78) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.12631 (89) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.14500 (87) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.14975 (24) uniform distribution in MR - rejecting arbitrary fit gca peak = 0.19357 (14) uniform distribution in MR - rejecting arbitrary fit gca peak Unknown = 0.94835 ( 0) gca peak Left_Cerebral_White_Matter = 0.07714 (104) gca peak Left_Cerebral_Cortex = 0.09712 (58) gca peak Left_Lateral_Ventricle = 0.16259 (20) gca peak Left_Inf_Lat_Vent = 0.16825 (27) gca peak Left_Cerebellum_White_Matter = 0.16765 (84) gca peak Left_Cerebellum_Cortex = 0.13902 (56) gca peak Left_Thalamus = 1.00000 (94) gca peak Left_Thalamus_Proper = 0.11131 (90) gca peak Left_Caudate = 0.15280 (69) gca peak Left_Putamen = 0.08324 (81) gca peak Left_Pallidum = 0.16930 (96) gca peak Third_Ventricle = 0.14975 (24) gca peak Fourth_Ventricle = 0.19357 (14) gca peak Brain_Stem = 0.08424 (78) gca peak Left_Hippocampus = 0.30264 (59) gca peak Left_Amygdala = 0.29869 (57) gca peak CSF = 0.23379 (36) gca peak Left_Accumbens_area = 0.70037 (62) gca peak Left_VentralDC = 0.14500 (87) 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_Cerebral_White_Matter = 0.07580 (103) gca peak Right_Cerebral_Cortex = 0.11620 (58) gca peak Right_Lateral_Ventricle = 0.17677 (13) gca peak Right_Inf_Lat_Vent = 0.24655 (23) gca peak Right_Cerebellum_White_Matter = 0.18739 (84) gca peak Right_Cerebellum_Cortex = 0.14777 (55) gca peak Right_Thalamus_Proper = 0.11793 (83) gca peak Right_Caudate = 0.30970 (66) gca peak Right_Putamen = 0.10360 (77) gca peak Right_Pallidum = 0.28129 (95) gca peak Right_Hippocampus = 0.24553 (55) gca peak Right_Amygdala = 0.33601 (57) gca peak Right_Accumbens_area = 0.45042 (65) gca peak Right_VentralDC = 0.12631 (89) 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 1.00 x + 0.0 estimating mean wm scale to be 1.00 x + 0.0 estimating mean csf scale to be 1.00 x + 0.0 setting left cbm cortex = 1.00 x + 0.00 setting right cbm cortex = 1.00 x + 0.00 saving intensity scales to aseg.auto_noCCseg.label_intensities.txt saving sequentially combined intensity scales to aseg.auto_noCCseg.label_intensities.txt 23554 voxels changed in iteration 0 of unlikely voxel relabeling 39 voxels changed in iteration 1 of unlikely voxel relabeling 0 voxels changed in iteration 2 of unlikely voxel relabeling 344 gm and wm labels changed (%100 to gray, % 0 to white out of all changed labels) 392 hippocampal voxels changed. 0 amygdala voxels changed. pass 1: 32267 changed. image ll: -5.372, PF=0.500 pass 2: 6290 changed. pass 3: 3011 changed. 17835 voxels changed in iteration 0 of unlikely voxel relabeling 16 voxels changed in iteration 1 of unlikely voxel relabeling 0 voxels changed in iteration 2 of unlikely voxel relabeling 6634 voxels changed in iteration 0 of unlikely voxel relabeling 10 voxels changed in iteration 1 of unlikely voxel relabeling 0 voxels changed in iteration 2 of unlikely voxel relabeling 7921 voxels changed in iteration 0 of unlikely voxel relabeling 22 voxels changed in iteration 1 of unlikely voxel relabeling 1 voxels changed in iteration 2 of unlikely voxel relabeling 0 voxels changed in iteration 3 of unlikely voxel relabeling 10136 voxels changed in iteration 0 of unlikely voxel relabeling 71 voxels changed in iteration 1 of unlikely voxel relabeling 6 voxels changed in iteration 2 of unlikely voxel relabeling 0 voxels changed in iteration 3 of unlikely voxel relabeling MRItoUCHAR: min=0, max=85 MRItoUCHAR: converting to UCHAR writing labeled volume to aseg.auto_noCCseg.mgz mri_ca_label utimesec 10636.834927 mri_ca_label stimesec 64.912876 mri_ca_label ru_maxrss 1280380928 mri_ca_label ru_ixrss 0 mri_ca_label ru_idrss 0 mri_ca_label ru_isrss 0 mri_ca_label ru_minflt 2434013 mri_ca_label ru_majflt 510 mri_ca_label ru_nswap 0 mri_ca_label ru_inblock 3 mri_ca_label ru_oublock 7 mri_ca_label ru_msgsnd 0 mri_ca_label ru_msgrcv 0 mri_ca_label ru_nsignals 0 mri_ca_label ru_nvcsw 813 mri_ca_label ru_nivcsw 7137900 auto-labeling took 187 minutes and 36 seconds. \n mri_cc -aseg aseg.auto_noCCseg.mgz -o aseg.auto.mgz -lta /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/transforms/cc_up.lta IXI_25_Guys_DTI_recon \n will read input aseg from aseg.auto_noCCseg.mgz writing aseg with cc labels to aseg.auto.mgz will write lta as /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/transforms/cc_up.lta reading aseg from /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/aseg.auto_noCCseg.mgz reading norm from /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/mri/norm.mgz 28267 voxels in left wm, 32301 in right wm, xrange [114, 131] searching rotation angles z=[-13 1], y=[-2 12] searching scale 1 Z rot 0.6 global minimum found at slice 124.0, rotations (4.11, -6.18) final transformation (x=124.0, yr=4.114, zr=-6.175): 0.99164 0.10757 0.07132 -15.45528; -0.10729 0.99420 -0.00772 41.93151; -0.07174 0.00000 0.99742 2.24310; 0.00000 0.00000 0.00000 1.00000; mri_cc: no WM voxels found with norm > 40 -- check skull stripping No such file or directory Darwin Renes-MacBook-Air-2.local 17.5.0 Darwin Kernel Version 17.5.0: Mon Mar 5 22:24:32 PST 2018; root:xnu-4570.51.1~1/RELEASE_X86_64 x86_64 recon-all -s IXI_25_Guys_DTI_recon exited with ERRORS at Mon Aug 6 19:33:20 -05 2018 For more details, see the log file /Volumes/TOSHIBA_EXT/freesurfer_subjects_dir/IXI_25_Guys_DTI_recon/scripts/recon-all.log To report a problem, see http://surfer.nmr.mgh.harvard.edu/fswiki/BugReporting

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Origin of freesusrfer output
by Ritesh Mahajan 07 Aug '18

07 Aug '18

External Email - Use Caution Hi Bruce, 1) Free-surfer output is always 256*256*256, regardless of any input dimensions. 2) I have a doubt, while doing this re-sampling from input dimension to 256*256*256. Does free-surfer change the origin of image? 3) My input is an MRI dicom image, for dicom tag value (0020,0032) which gives me the image position(origin). 4) How can i know the origin of free-surfer output in nii format? Do free-surfer change this value during processing? Can you please provide your valuable comments on this. Thanks, Ritesh Mahajan

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