[Freesurfer] What exactly are the BA_exvivo.thresh label and annotation files?
External Email - Use Caution Hello, The ex-vivo BA label and annotation files named ?h.BA??_exvivo.thresh.label and BA_exvivo.thresh.annot seem to be thresholded versions of the corresponding probabilistic BA labels. Was a simple threshold on the probability used and if yes, what was the value? In addition the annotation files, whether thresholded or not, only have one label per vertex. Are the labels based on the maximum probability across all BA labels? Thanks Julien -- -- Julien Besle Assistant Professor Department of Psychology Faculty of Arts and Sciences American University of Beirut Riad El-Solh / Beirut 1107 2020 Lebanon Jesup Hall, Room 103E Tel: +961 1 350 000 ext. 4927 - ___ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
[Freesurfer] convert BA probability labels to volume
External Email - Use Caution Hello, I'm trying to convert label files containing probability values for Brodmann areas (e.g. rh.BA1_exvivo.label) to volume files using mri_label2vol. I'd like to keep the probability value that's in the 5th column of the label file into the volume, but mri_label2vol sets all voxels in the label to 1 (i.e. creates a mask). Is there a way to do this? Thanks Julien -- -- Julien Besle Assistant Professor Department of Psychology Faculty of Arts and Sciences American University of Beirut Riad El-Solh / Beirut 1107 2020 Lebanon Jesup Hall, Room 103E Tel: +961 1 350 000 ext. 4927 - ___ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Re: [Freesurfer] MGN and LGN in ThalamicNuclei segmentation
External Email - Use Caution Thanks Juan. Nevermind. It turns out that I was comparing a discrete segmentation done with v10 (Freesurfer v6 or older) with posterior probability maps obtained using v12 (Freesurfer 7.0) in the same subject. The locations of the MGN and LGN segmentations have moved inferiorly in v12 compared to v10, but they match between the segmentation and the posterior probability maps in when using the same version, as they should. Other nuclei don't seem to have changed too much between v10 and v12. Thanks again! Julien ___ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
[Freesurfer] MGN and LGN in ThalamicNuclei segmentation
External Email - Use Caution
Hello,
I'm interested in locating the MGN and LGN using
segmentationThalamicNuclei, but there is a mismatch between their
location in the discrete segmentation (ThalamicNuclei.v10.T1.mgz) and
the underlying probability maps obtained by setting environment
variable WRITE_POSTERIORS to 1. While the LGN in the segmentation has
many voxels within the corresponding area of maximum probability, many
high-probability voxels are missing from it. For the MGN, the
segmentation volume is restricted to a small number of voxels in the
most lateral/posterior/superior part of the area of max probability, but
most high-probability voxels are absent from the segmentation. Any
reason why this could be happening? Is there anything I can do
(parameters I can change in the script) to fix this?
The defaut Freesurfer segmentation ("thalamus proper") is generally
larger than the segmentation output by segmentThalamicNuclei, except in
the area of the LGN, where the thalamic segmentation extends more
laterally/inferiorly, as if it had been extended in order to include the
LGN (although imperfectly). Unfortunately, this does not seem to be the
case for the MGN (which is my primary area of interest).
To solve the issue, I'm thresholding the posterior probability maps at
p>0.2 for both LGN and MGN and adding these voxels to the discrete
segmentation, but that's not very satisfactory. Actually, it wasn't very
clear to me from the published paper how the discrete segmentation is
obtained from the posterior probability maps and if any cut-off value is
used to decide whether to include any voxel in the final discrete
segmentation?
(Note that I'm using T1-weighted MPRAGE data at a resolution of 0.7 mm
isotropic)
Thanks
Julien
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Re: [Freesurfer] flirt.fsl error (NEWMAT::SingularException) when running bbregister in Freesurfer 7.0.0
External Email - Use Caution Hi Andrew, I was just wondering whether this issue has been fixed in version 7.1.0? Thanks Julien ___ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Re: [Freesurfer] flirt.fsl error (NEWMAT::SingularException) when running bbregister in Freesurfer 7.0.0
External Email - Use Caution Hi Andrew, Thanks for looking into this. Yes, copying the binary from the v6 to the v7 installation does solve the issue. Julien ___ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
[Freesurfer] flirt.fsl error (NEWMAT::SingularException) when running bbregister in Freesurfer 7.0.0
External Email - Use Caution Hi, I just installed freesurfer v7 and I'm getting an error in a script that calls bbregister with the --fslmat and --init-fsl options. This error does not occur in freesurfer v6 even when using exactly the same data, but it does also occur with a development version of freesurfer I downloaded in Sept 2019 (exact same error). The call is: DEBUG : 2020-05-06 12:07:12,816 : runCmd : Running: bbregister --s HLOSS_p5 --mov /home/julien/data/HLOSS/pilot05_B/DWI/B0_corrected_mean_resampled_MPRAGE.nii --reg /home/julien/data/HLOSS/pilot05_B/DWI/easy_lausanne_test/b0-TO-orig.dat --fslmat /home/julien/data/HLOSS/pilot05_B/DWI/easy_lausanne_test/b0-TO-orig.mat --init-fsl --dti The error occurs when bbregister calls fsl.flirt: INFO : 2020-05-06 12:08:24,560 : main : flirt.fsl -ref /home/julien/data/HLOSS/pilot05_B/DWI/easy_lausanne_test/tmp.bbregister.8331/fslregister/refvol.fslregister.nii -in /home/julien/data/HLOSS/pilot05_B/DWI/easy_lausanne_test/tmp.bbregister.8331/fslregister/movvol.fslregister.nii -bins 256 -cost corratio -dof 6 -searchrx -90 90 -searchry -90 90 -searchrz -90 90 -verbose 0 -omat /home/julien/data/HLOSS/pilot05_B/DWI/easy_lausanne_test/tmp.bbregister.8331/fslregister/fslmat0.trans.mat -schedule /usr/local/freesurfer/bin/fsl.5.0.2.xyztrans.sch -init /home/julien/data/HLOSS/pilot05_B/DWI/easy_lausanne_test/tmp.bbregister.8331/reg.init.dat.fsl.mat0 INFO : 2020-05-06 12:08:55,102 : main : Wed May 6 12:08:54 EEST 2020 INFO : 2020-05-06 12:08:55,603 : main : /mnt/f/data/HLOSS INFO : 2020-05-06 12:08:56,105 : main : flirt.fsl -ref /home/julien/data/HLOSS/pilot05_B/DWI/easy_lausanne_test/tmp.bbregister.8331/fslregister/refvol.fslregister.nii -in /home/julien/data/HLOSS/pilot05_B/DWI/easy_lausanne_test/tmp.bbregister.8331/fslregister/movvol.fslregister.nii -bins 256 -cost corratio -dof 6 -searchrx -90 90 -searchry -90 90 -searchrz -90 90 -verbose 0 -omat /home/julien/data/HLOSS/pilot05_B/DWI/easy_lausanne_test/tmp.bbregister.8331/reg.init.dat.fsl.mat -init /home/julien/data/HLOSS/pilot05_B/DWI/easy_lausanne_test/tmp.bbregister.8331/fslregister/fslmat0.trans.mat -schedule /usr/local/freesurfer/bin/flirt.newdefault.20080811.sch INFO : 2020-05-06 12:09:15,632 : main : terminate called after throwing an instance of 'NEWMAT::SingularException' INFO : 2020-05-06 12:09:15,633 : main : Abort (core dumped) INFO : 2020-05-06 12:09:15,634 : main : ERROR: flirt CRITICAL : 2020-05-06 12:09:15,634 : runCmd : Return Value: 1 It looks like the first time flirt.fsl is called everything goes fine, but the second time, the error occurs. Unfortunately this is not a script I wrote myself, so I'm not sure what this particular call to bbregister is supposed to achieve. I'm not sure the call to fsl.flirt depends on which version of FSL I have installed, but just in case, I used the FSL v6 and didn't change anything to the FSL installation between trying Freesurfer v6, dev or v7. I run everything on Ubuntu 16.04 running on WSL on Windows 10. Any idea what could be going wrong? Thanks Julien -- - Julien Besle Lagos Center, Apt 9A Sadat Street Beirut Lebanon tel: +961 78 980 317 - ___ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Re: [Freesurfer] Non-matching ROI areal measures using mri_segstats and mris_anatomical_stats (2nd post)
Hi Doug Indeed, you had answered my post previously, but so promptly that I missed it! My bad.. I have now re-run the analysis with the --jac option, and I do indeed now obtain the same results with both methods. Thanks a lot! Julien > Message: 17 > Date: Tue, 22 Sep 2015 10:03:56 -0400 > From: Douglas Greve<gr...@nmr.mgh.harvard.edu> > Subject: Re: [Freesurfer] Non-matching ROI areal measures using > mri_segstats and mris_anatomical_stats (2nd post) > To:freesurfer@nmr.mgh.harvard.edu > Message-ID:<56015fcc.8070...@nmr.mgh.harvard.edu> > Content-Type: text/plain; charset=windows-1252; format=flowed > > Sorry, I thought I had answered this (or something like it) recently. > When transforming area (or volume) with mri_surf2surf you have to turn > on jacobian correction with --jac. Try that and see if the results are > similar > doug > > > On 9/22/15 8:58 AM, julienbesle wrote: >> >I am reposting this message, as I didn't get any answer so far: >> >- >> > >> >Dear Freesurfer experts >> > >> >I have run a group ROI analysis comparing cortical thickness and area >> >between two groups of subject. I did this in two different ways: (1) >> >using mri_segstats after transforming each subject's data to fsaverage >> >space, AND (2) using mris_anatomical_stats after transforming the ROI >> >from fsaverage space to the space of each subjects. I get very similar >> >results for cortical thickness, but completely different results for >> >area. Does anyone have any idea why that could be happening ? >> > >> >Details: >> > >> >I have an ROI that I obtained from an atlas in MNI space and projected >> >to the fsaverage surface (into say ROI_lh.mgh file). The aim of the ROI >> >analysis was to find whether there are differences in cortical thickness >> >and area between two groups of subjects in this ROI. >> > >> >I tested this in two ways: >> > >> >Method 1: >> >a) I transformed the cortical thickness and area data of each subject >> >into fsaverage space >> > >> >mri_surf2surf --s subj --trgsubject fsaverage --hemi lh --sval area >> >--tval subj_area_fsaverage.mgh >> > >> >mri_surf2surf --s subj --trgsubject fsaverage --hemi lh --sval thickness >> >--tval subj_thickness_fsaverage.mgh >> > >> >b) I averaged the thickness or area data within the ROI in fsaverage >> >space for each subject using mri _segstats >> > >> >mri_segstats --seg ROI_lh.mgh --in subj_area_fsaverage.mgh --sum >> >output_area_subj.stats >> > >> >mri_segstats --seg ROI_lh.mgh --in subj_area_fsaverage.mgh --sum >> >output_thickness_subj.stats >> > >> >c) I used a 2-sample T test to compare the area or thickness output >> >between my two groups of subjects. >> > >> > >> >Method 2: >> >a) I transformed ROI.mgh into a label file ROI.label >> > >> >mri_cor2label --i ROI_lh.mgh --id 1 --l ROI_lh.label --surf fsaverage lh >> > >> >b) I transformed the label file from fsaverage space to each subject's space >> > >> >mri_label2label --srcsubject fsaverage --srclabel ROI_lh.label >> >--trgsubject subj --trglabel ROI_lh_subj.label --hemi lh --regmethod surface >> > >> >c) I averaged the thickness and area data within the ROI in each >> >subject's space using mris_anatomicalstats >> > >> >mris_anatomical_stats -l ROI_lh_subj.label -f output_subj.stats subj lh >> > >> >d) I used a 2 sample T test to compare the area or thickness data (from >> >the output_subj.stats files) between my two groups of subjects. >> > >> > >> >For cortical thickness, i obtain very similar results (not identical, >> >but similar to a hundredth of a mm), but for area, I get completely >> >different results, sometimes opposite direction of effect between the >> >two groups. I have 10 ROIs, and across ROIs, group differences are much >> >more significant in the first than the second method. The areal results >> >are in different units, which is expected (in the first method, they are >> >in mm2/vertex and in the second they are in mm2 because they express the >> >total area of the ROI). But despite that, shouldn't I get similar >> >patterns of results ? I would have assumed that the vertexwise areal >> >values averaged in the first method should somehow reflect differences >&
[Freesurfer] Non-matching ROI areal measures using mri_segstats and mris_anatomical_stats (2nd post)
I am reposting this message, as I didn't get any answer so far: - Dear Freesurfer experts I have run a group ROI analysis comparing cortical thickness and area between two groups of subject. I did this in two different ways: (1) using mri_segstats after transforming each subject's data to fsaverage space, AND (2) using mris_anatomical_stats after transforming the ROI from fsaverage space to the space of each subjects. I get very similar results for cortical thickness, but completely different results for area. Does anyone have any idea why that could be happening ? Details: I have an ROI that I obtained from an atlas in MNI space and projected to the fsaverage surface (into say ROI_lh.mgh file). The aim of the ROI analysis was to find whether there are differences in cortical thickness and area between two groups of subjects in this ROI. I tested this in two ways: Method 1: a) I transformed the cortical thickness and area data of each subject into fsaverage space mri_surf2surf --s subj --trgsubject fsaverage --hemi lh --sval area --tval subj_area_fsaverage.mgh mri_surf2surf --s subj --trgsubject fsaverage --hemi lh --sval thickness --tval subj_thickness_fsaverage.mgh b) I averaged the thickness or area data within the ROI in fsaverage space for each subject using mri _segstats mri_segstats --seg ROI_lh.mgh --in subj_area_fsaverage.mgh --sum output_area_subj.stats mri_segstats --seg ROI_lh.mgh --in subj_area_fsaverage.mgh --sum output_thickness_subj.stats c) I used a 2-sample T test to compare the area or thickness output between my two groups of subjects. Method 2: a) I transformed ROI.mgh into a label file ROI.label mri_cor2label --i ROI_lh.mgh --id 1 --l ROI_lh.label --surf fsaverage lh b) I transformed the label file from fsaverage space to each subject's space mri_label2label --srcsubject fsaverage --srclabel ROI_lh.label --trgsubject subj --trglabel ROI_lh_subj.label --hemi lh --regmethod surface c) I averaged the thickness and area data within the ROI in each subject's space using mris_anatomicalstats mris_anatomical_stats -l ROI_lh_subj.label -f output_subj.stats subj lh d) I used a 2 sample T test to compare the area or thickness data (from the output_subj.stats files) between my two groups of subjects. For cortical thickness, i obtain very similar results (not identical, but similar to a hundredth of a mm), but for area, I get completely different results, sometimes opposite direction of effect between the two groups. I have 10 ROIs, and across ROIs, group differences are much more significant in the first than the second method. The areal results are in different units, which is expected (in the first method, they are in mm2/vertex and in the second they are in mm2 because they express the total area of the ROI). But despite that, shouldn't I get similar patterns of results ? I would have assumed that the vertexwise areal values averaged in the first method should somehow reflect differences in area betwen subjects and therefore should give similar result to the total area approach (2nd method). Or is it that, in the first method, mri_surf2surf interpolates the vertexwise areal values without taking into account the stretching/deformation from the subject's space to fsaverage space (in contrast with a vertexwise analysis using mris_preproc) ? This is suggested by the fact that when I divide the total ROI area data obtained in the second method by the number of vertices in the ROI (in each subject's space), I end up with results that are very similar to the first method. The absolute values are different (around 0.7 mm2/vertex in the first method and around 0.6 mm2/vertex for the second method), but the group effects are in the same direction (across the 10 ROIs, all the effect sizes and p-values are similar so it can't be a coincidence). This suggests that the vertexwise areal values obtained in both methods simply reflect the ROI-average vertexwise areal values of each subject's mesh (and therefore do not include potential areal differences between subjects, assuming similar vertex spacing betwen subjects, and so shouldn't be used to compare areas between groups). However, if this is correct, isn't it strange that I should find significant differences in these vertexwise areal values between groups? So I guess I have three main questions: 1) Why is there a difference between the 2 methods for area but not thickness ? 2) What is the 'correct' method for area (if any) ? Or is there a better method for an ROI analysis of area? 3) Why are there even significant differences between vertexwise area values in the first and second method ? I am using Freesurfer v 5.3.0 (although the first analysis was potentially run using 5.0.0, not sure!) Thanks in advance Julien -- - Julien Besle Senior
[Freesurfer] Non-matching results for area ROI group analysis using two different approaches
Dear Freesurfer experts I have run an ROI analysis in Freesurfer using two different strategies and I would have expected the results to be the same (or similar), but they are not and I don't really understand why. I have an ROI that I obtained from an atlas in MNI space and projected to the fsaverage surface (into say ROI_lh.mgh file). The aim of the ROI analysis was to find whether there are differences in cortical thickness and area between two groups of subjects in this ROI. I tested this in two ways: 1. a) I transformed the cortical thickness and area data of each subject into fsaverage space mri_surf2surf --s subj --trgsubject fsaverage --hemi lh --sval area --tval subj_area_fsaverage.mgh mri_surf2surf --s subj --trgsubject fsaverage --hemi lh --sval thickness --tval subj_thickness_fsaverage.mgh b) I averaged the thickness or area data within the ROI for each subject using mri _segstats mri_segstats --seg ROI_lh.mgh --in subj_area_fsaverage.mgh --sum output_area_subj.stats mri_segstats --seg ROI_lh.mgh --in subj_area_fsaverage.mgh --sum output_thickness_subj.stats c) I used a 2-sample T test to compare the area or thickness output between my two groups of subjects. 2. a) I transformed ROI.mgh into a label file ROI.label mri_cor2label --i ROI_lh.mgh --id 1 --l ROI_lh.label --surf fsaverage lh b) I transformed the label file from fsaverage space to each subject's space mri_label2label --srcsubject fsaverage --srclabel ROI_lh.label --trgsubject subj --trglabel ROI_lh_subj.label --hemi lh --regmethod surface c) I averaged the thickness and area data within the ROI using mris_anatomicalstats mris_anatomical_stats -l ROI_lh_subj.label -f output_subj.stats subj lh d) I used a 2 sample T test to compare the area or thickness data (from the output_subj.stats files) between my two groups of subjects. For cortical thickness, i obtained very similar results (not identical, but similar to a hundredth of a mm), but for area, i get completely different results, sometimes opposite direction of effect between the two groups. I have 10 ROIs, and across ROIs, group differences are much more significant in the first than the second method. The areal results are in different units, which is expected (in the first method, they are in mm2/vertex and in second they are in mm2 because they express the total area of the ROI). But despite that, shouldn't I get similar patterns of results ? I would have assumed that the vertexwise areal values averaged in the first method should somehow reflect differences in area betwen subjects and therefore should give similar result to the total area approach (2nd method). Now for the weird part: When I divide the total ROI area data obtained in the second method by the number of vertices in the ROI (in each subject's space), I end up with results that are very similar to first method! The absolute values are different (around 0.7 mm2/vertex in the first method and around 0.6 mm2/vertex for the second method), but the group effects are in the same direction (across the 10 ROIs, all the effect sizes and p-value are similar so it can't be a coincidence). I can't get my head around this: assuming that the spacing between vertices of the mesh is similar between different subjects, why are there even significant differences between groups? Or is that not an assumption that can be made ? (I should add that these are relatively large groups: 73 vs 55) So I guess I have three main questions: 1) Why is there a difference between the 2 methods for area but not thickness ? 2) What is the 'correct' method for area (if any) ? Or is there a better method for an ROI analysis of area? 3) Why are there even significant differences between vertexwise area values in the second method ? I am using Freesurfer v 5.3.0 (although the first analysis was potentially run using 5.0.0, not sure!) Thanks in advance Julien ___ Freesurfer mailing list Freesurfer@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.
