Freesurfer October 2015

freesurfer@nmr.mgh.harvard.edu

142 participants
214 discussions

Checking optseq efficiency of a custom par file.
by Sam Zorowitz 24 Nov '15

24 Nov '15

Dear Freesurfer list, Using the optseq2 program, is it possible to calculate the efficiency of a custom par file? I have an fMRI task that will be split into three blocks. I want to calculate the overall efficiency of my overall design byconcatenating the best par file from optimizing each individual block. I have already tried doing so by concatenating the three par files (updating the onset times) and inputting this into optseq2 by: >> optseq2 --in new_file.par --nosearch --tr 1.75 --ntp 1080 --psdwin 0 3.5 1.75 --o new_dir If I do this, however, I get a "core dump" error. Does anyone know how I might going about doing this? I've attached the new_par file for convenience. Best, sam

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Extracing values from ces.nii
by Afzal, Afsana 04 Nov '15

04 Nov '15

Hi, I'm trying to extract the contrast values from ces.nii.gz after first-level analysis. My goal is to average the contrast values for each voxel across subjects for a given condition and see where an individual from a separate population falls within the distribution of contrast values. The ces.nii file I'm working with has the following dimension: (27307, 1, 6, 1), which I interpreted as containing information about 27307 voxels in a 3D matrix. What does the information in the 6 rows for each voxel represent? I was expecting to get a single raw b-value for each voxel. The structure is consistent with sig.nii and t.nii files as well. Thanks for any help, Afsana ______________________________ Afsana Afzal Clinical Research Coordinator Massachusetts General Hospital Division of Neurotherapeutics Department of Psychiatry: Neurosciences 149 13th St, Room 2612 Charlestown, MA 02129 Phone: 617-643-5129 Fax: 617-726-4078

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changing the index of labels
by Jacobs H (NP) 04 Nov '15

04 Nov '15

Hi, Is there a way to change the index of the segmentation of the hippocampal subfields, so that when I combine left and right, FreeSurfer treats them as different regions? Thanks! Best Heidi > >>I just checked again in freeview and indeed they have the same index >>(e.g. >>CA1 has value 206 for left and also for right). >> >>On 10/27/15, 5:01 PM, "Douglas Greve" <greve(a)nmr.mgh.harvard.edu> wrote: >> >>>The color is not important. The question is whether they have a >>>different index. Can you confirm that lh and rh have the same index? >>> >>>On 10/27/15 11:53 AM, Jacobs H (NP) wrote: >>>> Hi Doug, >>>> >>>> Yes, for the aseg they are. But not for the hippocampal subfields: >>>>left >>>> and right have the same color coding. >>>> I am creating one segmentation, including left and right hippocampal >>>> subfields and aparc, for partial volume correction. >>>> Any idea how I can make the labels for the hippocampal subfields >>>>different >>>> (freesurfer version 6)? >>>> >>>> Thanks >>>> Heidi >>>> >>>> On 10/27/15, 4:32 PM, "Douglas Greve" <greve(a)nmr.mgh.harvard.edu> >>>>wrote: >>>> >>>>> The indices should be different. Eg, 17 is left hippo, 53 is right >>>>> hippo. If you click on them in freeview and different labels appear, >>>>> then FS knows they are different >>>>> >>>>> On 10/24/15 9:29 PM, Jacobs H (NP) wrote: >>>>>> Hi. >>>>>> >>>>>> Just one another related question: now that I was able to combine >>>>>>left >>>>>> and >>>>>> right hippocampal subfields with the aparc-aseg correctly, I noticed >>>>>> that >>>>>> the left and right hippocampal subfields have the same color labels >>>>>>and >>>>>> codes. What would be the best way to make sure that FreeSurfer >>>>>> understand >>>>>> that the left and right subfields (e.g. Left and right CA1) are >>>>>> different >>>>>> areas? >>>>>> >>>>>> Thanks! >>>>>> Heidi >>>>>> >>>>>> On 10/21/15, 11:01 PM, "Jacobs H (NP)" >>>>>> <h.jacobs(a)maastrichtuniversity.nl> >>>>>> wrote: >>>>>> >>>>>>> Thanks! Works wonderful! >>>>>>> Heidi >>>>>>> >>>>>>> On 10/21/15, 10:50 PM, "Douglas N Greve" >>>>>>><greve(a)nmr.mgh.harvard.edu> >>>>>>> wrote: >>>>>>> >>>>>>>> If you want to remove them, you can use mri_binarize with the >>>>>>>> --replace >>>>>>>> option, replacing them with whatever you want. >>>>>>>> >>>>>>>> On 10/21/2015 04:38 PM, Jacobs H (NP) wrote: >>>>>>>>> Hi, >>>>>>>>> >>>>>>>>> I am trying to generate a segmentation file containing the >>>>>>>>>aseg+aparc >>>>>>>>> but replacing the hippocampus with the hippocampal subfields. >>>>>>>>> With mergeseg I was able to merge the segmentations, but >>>>>>>>> unfortunately >>>>>>>>> parts of the ³old² hippocampus (labeled as 17 and 53) are still >>>>>>>>>in >>>>>>>>> there (as the area covered by the subfields is not 100% equal to >>>>>>>>>the >>>>>>>>> hippocampus of the aseg). >>>>>>>>> How can I remove the remains of the old hippocampal labels? >>>>>>>>> >>>>>>>>> Many thanks! >>>>>>>>> Best >>>>>>>>> Heidi >>>>>>>>> >>>>>>>>> >>>>>>>>> _______________________________________________ >>>>>>>>> Freesurfer mailing list >>>>>>>>> Freesurfer(a)nmr.mgh.harvard.edu >>>>>>>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >>>>>>>> -- >>>>>>>> Douglas N. Greve, Ph.D. >>>>>>>> MGH-NMR Center >>>>>>>> greve(a)nmr.mgh.harvard.edu >>>>>>>> Phone Number: 617-724-2358 >>>>>>>> Fax: 617-726-7422 >>>>>>>> >>>>>>>> Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting >>>>>>>> FileDrop: https://gate.nmr.mgh.harvard.edu/filedrop2 >>>>>>>> www.nmr.mgh.harvard.edu/facility/filedrop/index.html >>>>>>>> Outgoing: >>>>>>>> ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/ >>>>>>>> >>>>>>>> _______________________________________________ >>>>>>>> Freesurfer mailing list >>>>>>>> Freesurfer(a)nmr.mgh.harvard.edu >>>>>>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >>>>>>>> >>>>>>>> >>>>>>>> The information in this e-mail is intended only for the person to >>>>>>>> whom it >>>>>>>> is >>>>>>>> addressed. If you believe this e-mail was sent to you in error and >>>>>>>>the >>>>>>>> e-mail >>>>>>>> contains patient information, please contact the Partners >>>>>>>>Compliance >>>>>>>> HelpLine at >>>>>>>> http://www.partners.org/complianceline . If the e-mail was sent to >>>>>>>> you in >>>>>>>> error >>>>>>>> but does not contain patient information, please contact the >>>>>>>>sender >>>>>>>> and >>>>>>>> properly >>>>>>>> dispose of the e-mail. >>>>>>>> >>>>>> _______________________________________________ >>>>>> Freesurfer mailing list >>>>>> Freesurfer(a)nmr.mgh.harvard.edu >>>>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >>>>>> >>>>>> >>>>> _______________________________________________ >>>>> Freesurfer mailing list >>>>> Freesurfer(a)nmr.mgh.harvard.edu >>>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >>>> >>>> _______________________________________________ >>>> Freesurfer mailing list >>>> Freesurfer(a)nmr.mgh.harvard.edu >>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >>>> >>>> >>> >>>_______________________________________________ >>>Freesurfer mailing list >>>Freesurfer(a)nmr.mgh.harvard.edu >>>https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >> >

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Re: [Freesurfer] A mixed effect model approach in within subject dataset {Disarmed}
by pablo najt 03 Nov '15

03 Nov '15

Dear FS experts.I have query about a relating to a previous email (below). I am aiming to run a LME analysis on cross-sectional data from different families and have variable 'family' (number of families) as my NI vector. My design has three groups and therefore I am not able to use qdec. I am running the matlab commands below and finding some difficulty would really appreciate if you could help out.ThanksPablo Start analysis as follows: 1-Read your label eg.: lhcortex = fs_read_label('freesurfer/subjects/fsaverage/label/lh.cortex.label'); 2-Read the data file eg.: [lhY, lhmri] = fs_read_Y('lh.thickness.mgh'); %---------------------I input the concatenated .mgh image from preproc and mris_surf2surf-----------------------------------------------------------------------% 3-Fit a vertex-wise lme model with random effects.: lhstats = lme_mass_fit_vw(X, [1 2], lhY, ni, lhcortex); Here I am getting the following problems:%-------------------- If I use number of families as my ni get the following------------------------------------------------------------------------------------------------%lhstats = lme_mass_fit_vw(X, [1 2], lhY, 82, lhcortex);Error using lme_mass_fit (line 108)The total number of measurements, indicated by sum(ni), mustbe the same as the number of rows of the designmatrix X Error in lme_mass_fit_vw (line 73)[stats1,st1] = lme_mass_fit(X,[],Xrows,Zcols,Y,ni,prs,e); My matrix is organised in "family", "group", Sex" and "age" columns". 4-Perform vertex-wise inference eg.: CM.C = [your contrast matrix]; F_lhstats = lme_mass_F(lhstats, CM); 5-Save results eg.: fs_write_fstats(F_lhstats, lhmri,' sig.mgh', 'sig'); Date: Thu, 10 Sep 2015 13:44:36 +0000 From: jbernal0019(a)yahoo.es To: freesurfer(a)nmr.mgh.harvard.edu Subject: Re: [Freesurfer] A mixed effect model approach in within subject dataset Hi Pablo I think you can use LME to analyze your data by ordering the rows of your design matrix appropriately. You can consider all subjects belonging to the same family as if they were a single subject in a longitudinal analysis. You can put in your design matrix all subjects belonging to family1 first, then all subjects belonging to family 2 and so on. Then the 'ni' required by lme_mass_fit_vw is a vector with the number of subjects in each family as its entries (ordered according to your design matrix). So the length of the 'ni' vector is equal to the number of different families in your data. Now you can go further and additionally order the rows of your design matrix within each family by age. This will allow you to test the effect of age within family. When choosing the random effects for your statistical model remember that a random effect can only be the intercept term or any covariate that varies within family. For example you can compare a model with a single random effect for the intercept term against the same model but considering both the intercept term and age as random effects. Hope that helps Cheers -Jorge De: pablo najt <pablonajt(a)hotmail.com> Para: "freesurfer(a)nmr.mgh.harvard.edu" <freesurfer(a)nmr.mgh.harvard.edu> Enviado: Jueves 10 de septiembre de 2015 8:07 Asunto: [Freesurfer] A mixed effect model approach in within subject dataset Dear Freesurfer users,I wanted to enquire if anyone had successfully been able to implement Bernal's Linear Mixed Effects (LME) Models in cross-section dataset *not longitudinal* (please see previous thread below). I am willing to perform a LME (3 groups (HC, PT and Unaffected_relatives) and 3 covariates (sex, age, and family) with "family" variable been a within-subject factor. LME will allow to control for the non-independence of data contributed by patients and relatives from the same families.Thanks in advance!Pablo From: michaelnotter(a)hotmail.com To: freesurfer(a)nmr.mgh.harvard.edu Date: Wed, 19 Feb 2014 13:10:09 +0100 Subject: [Freesurfer] Analysis of structural data acquired from multiple sites by using a mixed effect model approach Hi everybody, I want to compare the surface data of 3 groups (GroupA, GroupB and Controlls) but have the problem that they were acquired from 4 different scanner sites. As I can see it, there are three ways how I could tackle this problem: 1. I could use mri_glmfit and create a qdec table / fsgd-file with 12 classes: Class GroupA_site1; Class GroupA_site2,... And then use the contrasts [0.25 0.25 0.25 0.25 0 0 0 0 -0.25 -0.25 -0.25 -0.25] to compare GroupA to the Controlls. My Problem with this approach is, that the sites don't contribute the same amount of subjects to the analysis. I'm not sure if this could be handled by simply using a weighted contrast. Meaning, if Site1 and Site2 had twice as many subjects than Site3 and Site4, I could modify the contrast to [0.33 0.33 0.17 0.17 0 0 0 0 -0.33 -0.33 -0.17 -0.17]. 2. I could create dummy variables to account for the variability between sites. In this case, I only need to specify 3 classes (Class GroupA; Class GroupB; Class Controlls) in my fsgd-file. And I use a design matrix that has 4 dummy variables at the end, which specify to which site a subject belongs. This approach might work, but I'm not confident that it is the right one. 3. I could use a mixed effect model approach and specify site as a random effect. If I understand it correctly, the mixed effect model approach would be the best one, as it accounts for the variability within sites. Is that correct or are there other issues/better approaches? I tried to implement a mixed effect model by using Bernal's Linear Mixed Effects (LME) Models (http://surfer.nmr.mgh.harvard.edu/fswiki/LinearMixedEffectsModels) but run into some problems. I'm not sure if LME can only be applied on longitudinal data or if my implementation is wrong. I have a design matrix X that specifies the characteristics of each subject per row as follows: Intercept GroupA GroupB Controll Age IQ Site1 Site2 Site3 Site4 1 1 0 0 11.1 99 0 0 1 0 1 0 1 0 11.1 101 0 0 1 0 1 1 0 0 11.4 95 1 0 0 0 1 0 0 1 12.4 100 1 0 0 0 ... As I have no repeated measures, 'ni' is just a vector with length X containing '1's. If I do now the vertex-wise linear mixed-effects estimation, I get the following output: >> stats = lme_mass_fit_vw(X,[7 8 9 10],Y,ni,lhcortex); Starting matlabpool using the 'local' profile ... connected to 8 workers. Starting model fitting at each location ... Location 24994: Index exceeds matrix dimensions. Location 24994: Algorithm did not converge. Initial and final likelihoods: -10000000000, -10000000000. Location 62484: Index exceeds matrix dimensions. Location 62484: Algorithm did not converge. Initial and final likelihoods: -10000000000, -10000000000. ... I've checked the matrix dimensions of X, Y, ni and lhcortex and compared them to the LME mass_univariate example stored in ADNI_Long_50sMCI_vs_50cMCI.mat but couldn't find any divergence. Has anybody encountered similar problems? Is my approach of specifying 'ni' as a vector of'1's even legitimate? Thanks, Michael _______________________________________________ Freesurfer mailing list Freesurfer(a)nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Partners Compliance HelpLine at http://www.partners.org/complianceline . If the e-mail was sent to you in error but does not contain patient information, please contact the sender and properly dispose of the e-mail. _______________________________________________ Freesurfer mailing list Freesurfer(a)nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Partners Compliance HelpLine at http://www.partners.org/complianceline . If the e-mail was sent to you in error but does not contain patient information, please contact the sender and properly dispose of the e-mail. _______________________________________________ Freesurfer mailing list Freesurfer(a)nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Partners Compliance HelpLine at http://www.partners.org/complianceline . If the e-mail was sent to you in error but does not contain patient information, please contact the sender and properly dispose of the e-mail.

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cortical thickness - comparing two groups within a ROI
by Eryilmaz, H. Hamdi 03 Nov '15

03 Nov '15

Dear FS experts, I have a question about extracting average cortical thickness from a manually created ROI. I am comparing 2 groups, namely PostFort and PreFort and my fsgd file appears as the following: GroupDescriptorFile 1 Title PostPreFortification Class PostFort Class PreFort Input Subject1 PostFort Input Subject2 PostFort . . . The contrast that I use to compare these groups is [1 -1]. When I display the significance map for this contrast I get the following image on the left hemisphere: [X] My first question is, those blue clusters represent regions, where thickness is greater in the PreFort group, don't they? Assuming this is correct, I created a label for this region (which contains about 3000 vertices) and extracted the thickness value from this region for each subject using the following commands. These commands are part of scripts in which $subject and $label are defined. [X] to make a label for each subject (the original label was created on fsaverage): mri_label2label --srclabel $SUBJECTS_DIR/labels/${label}.label --srcsubject fsaverage --trglabel $SUBJECTS_DIR/$subject/label/$label.label --trgsubject $subject --regmethod surface --hemi lh to create a stats file of this ROI containing several anatomical measures: mris_anatomical_stats -f $SUBJECTS_DIR/$subject/stats/lh.NP_PostMINUSPre_IPS.label.stats -l $SUBJECTS_DIR/$subject/label/NP_PostMINUSPre_IPS.label $subject lh to compile thickness values from all subjects into one table: aparcstats2table --hemi lh --subjectsfile $SUBJECTS_DIR/Subject_Files/RPDR/214_PrePostFort --parc NP_PostMINUSPre_IPS.label --meas thickness --tablefile $SUBJECTS_DIR/Analyses_Thickness/Tables/LH_NP_PostMINUSPre_IPS_stats.txt This table displays the average thickness value of my ROI for each subject. Based on this table I calculated the mean thickness for each group, which is as the following: PostFort: 3.043 PreFort: 2.842 My question is: If this cluster appears blue in the Post>Pre map, shouldn't the thickness have been greater in the PreFort group? Or am I missing a step? Many thanks in advance! Best, Hamdi

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R: Re: average z-score of each subject from a common cluster
by stdp82＠virgilio.it 03 Nov '15

03 Nov '15

Thanks.I have obtained: $Id: mri_segstats.c,v 1.75.2.9 2013/02/16 00:09:33 greve Exp $ cwd cmdline mri_segstats --seg z.nii.gz --annot Control21_FS rh aparc --i z.nii.gz --sum summaryfile sysname Darwin hostname iMac-di-Stefano.local machine x86_64 user Stefano UseRobust 0 Loading z.nii.gz Loading z.nii.gz Voxel Volume is 1 mm^3 Generating list of segmentation ids Found 22 segmentations Computing statistics for each segmentation 0 -7 2 2.000 1 -6 110 110.000 2 -5 255 255.000 3 -4 518 518.000 4 -3 1190 1190.000 5 -2 1692 1692.000 6 -1 4104 4104.000 7 0 61577 61577.000 8 1 42598 42598.000 9 2 28146 28146.000 10 3 14859 14859.000 11 4 5845 5845.000 12 5 1899 1899.000 13 6 485 485.000 14 7 116 116.000 15 8 75 75.000 16 9 74 74.000 17 10 78 78.000 18 11 65 65.000 19 12 104 104.000 20 13 45 45.000 21 14 5 5.000 How I can know the meaning of this number? Where is z? I have tried also with:mri_segstats --seg z.nii.gz --annot Control_21 rh aparc --i z.nii.gz --sum summaryfile --mask .../fc.ramgseed.surf.rh/R_Amygdala/my-glm.wls/group.diff/cache.th13.neg.sig.masked.nii.gz --avgwfvol mrivol but I have problem with interpretation. Stefano ----Messaggio originale---- Da: greve(a)nmr.mgh.harvard.edu Data: 30-ott-2015 16.17 A: <freesurfer(a)nmr.mgh.harvard.edu> Ogg: Re: [Freesurfer] average z-score of each subject from a common cluster On 10/30/15 7:16 AM, stdp82(a)virgilio.it wrote: Hi list, I have two queries, please. I'd like to have the z-score from my rsfMRI data (seed-analyis). 1) I have extract the z-score from the Vtx Max In details, after groups comparison analysis, I have opened the cache.th13.pos.sig.cluster.summary contained in group.diff folder and I have read the Vtx Max coordinates. Next, I have open the z.nii.gz of each subject and I have expected the z-score from the vertex which have the Vtx Max coordinates. Is this procedure corrected? Yes 2) z-score of each subject from a common cluster I would like to use the cluster which shows the group difference (cache.th13.pos.sig.cluster.nii.gz) as ROI mask. Thus, I would extract from it the average of the z-score which is contained in each subject. How should I do? Use mri_segstats passing the z map as the input (--i) and the cluster map as the seg. The output will be --sum. Run with --help for more info Thanks. Stefano _______________________________________________ Freesurfer mailing list Freesurfer(a)nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer

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R: Re: error vcsf.config
by stdp82＠virgilio.it 03 Nov '15

03 Nov '15

Yes, the ventricle is very small. The segmentation in aparc and aseg is nice.How can I do to analyze this subject? I need to include it in the analysis.Many thanks, Stefano ----Messaggio originale---- Da: greve(a)nmr.mgh.harvard.edu Data: 30-ott-2015 16.03 A: <freesurfer(a)nmr.mgh.harvard.edu> Ogg: Re: [Freesurfer] error vcsf.config That means it could not find any CSF voxels. Try checking the registration. It could also be that this is a subject with really small ventricles. On 10/30/15 3:57 AM, stdp82(a)virgilio.it wrote: Hi list, During fcseed-sess -s subj -cfg vcsf.config a subject produces the follow error. I have rerun recon-all, cheched aparc+aseg with tkmedit. They seem to be ok. Why this error is produced? Thanks Stefano Creating output directory /Applications/freesurfer/subjects/fMRI/subj/rest/001/tmp.fcseed-sess.39124/glm Loading y from /Applications/freesurfer/subjects/fMRI/subj/rest/001/fmcpr.nii.gz Saving design matrix to /Applications/freesurfer/subjects/fMRI/subj/rest/001/tmp.fcseed-sess.39124/glm/Xg.dat Normalized matrix condition is 61.5872 Matrix condition is 1e+08 Pruning voxels by thr: 0.000000 Found 0 voxels in mask Saving mask to /Applications/freesurfer/subjects/fMRI/subj/rest/001/tmp.fcseed-sess.39124/glm/mask.mgh search space = 0.000000 DOF = 297 Starting fit and test Fit completed in 0.0008 minutes Computing temporal AR1 Writing results Computing FSNR mean maxvox sig=0 F=0 at index 0 0 0 seed=1446518089 linear maxvox sig=0 F=0 at index 0 0 0 seed=1446518089 quad maxvox sig=0 F=0 at index 0 0 0 seed=1446518089 Computing PCA (300) ERROR: no voxels in mask _______________________________________________ Freesurfer mailing list Freesurfer(a)nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer

2 1

reproducing sig.mgh
by Eric Cunningham 03 Nov '15

03 Nov '15

Hello Freesurfer Experts, I am trying to reproduce the values in sig.mgh using matlab, just to confirm that I know what is going on. My numbers do not match exactly, and I am hoping someone can explain my error, or point me in the right direction. With Qdec, I built a model with one discrete factor (A) with groups (A1) and (A2), one continuous covariate (B), and one nuisance factor (C). I extracted the values from sig.mgh from the folder: lh-Diff-A1-A2-Cor-area-B at a specific vertex. I also extracted the values from y.mgh at the same vertex. I then ran an anova with contrast matrix, and expected the -log10(p-value) of the A*B term to match that of sig.mgh. [1 0 0;... (A) 0 1 0;... (B) 0 0 1;... (C) 1 1 0]; (A*B) Thank you for your time, -E

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FreeSurfer and OpenMP
by Linda BOUMGHAR 03 Nov '15

03 Nov '15

I would like to use freesurfer with OpenMP, with 4 processors. I wrote this : recon-all -all -i /mnt/linuxwin/lboumgha/data/CENTER_TBI/tro/suj1/T1.nii.gz -subjid subj1 -openmp <8> and I got this error message : bash: syntax error near unexpected token `8' What is the good syntax if I want tu use OpenMP, please? Great regards, Linda Boumghar ---------------------------------------------------------------- This message was sent using IMP, the Internet Messaging Program.

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Voxel based vs surface based
by John Anderson 03 Nov '15

03 Nov '15

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Freesurfer October 2015