Freesurfer

freesurfer@nmr.mgh.harvard.edu

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30127 discussions

Trouble finding recent archives
by Dierker, Donna 05 Aug '26

05 Aug '26

External Email - Use Caution I'm having trouble finding the mailing list archives. This exists, but I can't find more recent messages: https://secure-web.cisco.com/1_AzCMVLSYPWXrEp1K-AJyCtXx9QQ9JDRC8EUf3bu9E09G… The archives link here says Forbidden: https://secure-web.cisco.com/1t7pgqdKCNN4T1zl63JGJU0ZpokAYt_RliqFTp2CWPt9AG… Thanks, Donna ________________________________ The materials in this message are private and may contain Protected Healthcare Information or other information of a sensitive nature. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this email in error, please immediately notify the sender via telephone or return mail.

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Question: Manual control points in FreeSurfer 8.2 are read as 0 points by mri_normalize
by Deborah Pou 04 Aug '26

04 Aug '26

External Email - Use Caution Hi, I am needing some help with control points. Environment: - FreeSurfer 8.2.0 - Ubuntu 22.04 on WSL2 I am trying to manually edit a subject using control points for intensity normalization. Workflow: 1. Open the subject in Freeview. 2. Create a new Point Set. 3. Save it as "Control Points" into: SUBJECT/tmp/control.dat 4. Run: recon-all -s SUBJECT -autorecon2-cp -autorecon3 The recon-all log shows: mri_normalize -f SUBJECT/tmp/control.dat ... using control points from file SUBJECT/tmp/control.dat... However, immediately afterwards it reports: Reading 0 control points... error: MRI3dGentleNormalize: mean = 0.0, nctrl = 0 The command completes, but the manually placed control points are ignored. As a verification, I compared the original and edited normalization volumes: mri_diff original/mri/norm.mgz edited/mri/norm.mgz Output: diffcount 0 which indicates that intensity normalization was unchanged. Am I doing something wrong? Is this the expected behavior in FreeSurfer 8.2, or is there an issue with how Freeview writes control.dat?

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Misidentification of the central sulcus in fsaverage registration
by Mitchell, Mackenzie 04 Aug '26

04 Aug '26

External Email - Use Caution Hello, We are seeing that in some cases (13/167 subjects) FreeSurfer v7.3.2 incorrectly labeled the central sulcus in at least one hemisphere (see example below). In all cases, FreeSurfer is labeling the postcentral sulcus as the central sulcus. In one case, this is happening twice for the same subject who participated in two independent projects (i.e., we find this issue with different T1s and Freesurfer runs). See example below. [HUBS05_RH_looksincorrect.png] We have checked the segmentations and alignments for all subjects and they all look correct. We think this may be happening at the stage of normalization to fsaverage. Most critically for us, it looks like this error is displacing the mapping of our functional data to the surface, as the motor network functional connectivity maps are shifted forward, as would be expected from the mislabeling. See example below. [Bilateral motor FC.png] In an attempt to resolve this issue, we have run FreeSurfer v8.2.0 on these 13 subjects. This resulted in the central sulcus being correctly identified in only 4/13 subjects. Searching through past posts to this mailing list, we found this thread (https://secure-web.cisco.com/18f5PAXmePTLSv04gGyGwEsaY9MJkKjxLyhKbYkcEUbMBl…) which suggested to rotate the spherical registration (e.g., z+15 degrees). We found that with various rotation parameters we could improve the cortical parcellation in a handful of subjects. However, we do not currently use the cortical parcellations for our work and our primary concern is being able to accurately map functional data to the surface. We are not sure if spherical rotation is the right point/method to intervene. All insight on how to intervene to improve fsaverage normalization would be greatly appreciated. Thank you, Mackenzie

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Request for FreeSurfer License for Academic Research Use
by bhwang1228 03 Aug '26

03 Aug '26

External Email - Use Caution Dear FreeSurfer Team, I am writing to request a FreeSurfer license for academic research use. I am a researcher working on neuroimaging analyses using UK Biobank brain MRI-derived phenotypes. The software will be used only for non-commercial academic research and data visualization purposes. Thank you very much for your help. Best regards, Binghan Wang

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infant_recon_all is missing from ubuntu 24 8.2.0 deb package
by Vladimir Vainer 28 Jul '26

28 Jul '26

External Email - Use Caution Hi, I've recently tried using infant_recon_all on latest ubuntu 24 8.2.0 deb package, and I couldn't find it there. It looks like it's completely missing there. It is present in ubuntu 22 8.2.0 deb package though. -- If you can't explain it *simply*, you don't understand it well enough. - Albert Einstein

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Expected magnitude of regional offset between gtmseg and aparc+aseg for no-PVC PET extraction?
by Carme Uribe 23 Jul '26

23 Jul '26

External Email - Use Caution Dear Dr. Greve & FreeSurfer developers, I am comparing two FS-based ROI extraction strategies for a dynamic PET study ([18F]SynVesT-1, FreeSurfer 8.1.0), both using the Desikan–Killiany parcellation and an identical, volume-sampled centrum semiovale reference region. Regional binding potentials (BPnd, SRTM2) were derived from tacs without partial-volume correction using: 1. aparc+aseg volumetric labels (1 mm) in the T1 native space; 2. gtmseg labels (leveraging the gtmseg tool in PETsurfer), same DK parcels (no editions to the gtmseg.mgz). Across the 68 cortical ROIs the two agree extremely well as expected, but gtmseg regional BPnd is systematically ~21% higher than aparc+aseg (and reported BPnd values in the lit using the same reference region) consistent across subjects and regions. I understand these are the same parcellation scheme but not the same segmentation: gtmseg defines the cortical ribbon from the white/pial surfaces at 0.5 mm, whereas aparc+aseg uses the 1 mm voxel ribbon. My interpretation is that, without PVC, the surface-defined ribbon recovers purer? GM (less WM/CSF dilution), which would explain a positive offset in this direction. But, my doubts: 1. Is a systematic ~20% higher regional mean from gtmseg vs aparc+aseg, under no-PVC extraction, of the expected magnitude in your experience, or does it point to something we may be doing wrong? 2. For no-PVC regional extraction specifically, which segmentation do you consider the more appropriate substrate, given that gtmseg is optimised as the input geometry for mri_gtmpvc rather than for direct sampling? Thank you very much for any guidance and the great efforts put on surface-based methodologies! Best wishes, Carme Uribe CAMH, Toronto

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How to check surface registration accuracy
by Alex 19 Jul '26

19 Jul '26

External Email - Use Caution Dear experts, I have a basic question regarding quality control for surface-based registration. In volume-based analysis, I usually check registration by overlaying the transformed image on the target image. What is the recommended way to do this for surface-based registration? Currently, my practice is to visually inspect the Desikan-Killiany parcellation overlay on the native surface, under the assumption that a reasonable parcellation result would indicate satisfactory registration. I chose the DK atlas because its gyral-based labels are relatively easy to recognize on the native surface. Is this practice sufficient, or are there better practices I should follow? Thank you for your time! Yang Hu

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Differences between mri_surf2surf and mris_ca_label for cortical parcellation
by Alex 15 Jul '26

15 Jul '26

External Email - Use Caution Dear experts, As far as I know, there are two common ways to assign anatomical labels to cortical vertices: using mri_surf2surf (combined with an atlas annot file) and using mris_ca_label (which relies on a pre-trained classifier). My question is: in practice, which method is preferable? Is mris_ca_label theoretically more accurate, but in reality the two yield nearly identical results? Or are there systematic, non-negligible differences? Also, is mris_ca_label less robust than the simpler projection method, particularly in subjects with imperfect surface reconstruction. Thank you for your advice. Yang Hu

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Choroid plexus volumes zeroed out in aseg.stats
by Chholak, Parth (NIH/NIAAA) [F] 14 Jul '26

14 Jul '26

External Email - Use Caution Hello FreeSurfer Developers, I need to compute volumes of different brain regions using T1 MPRAGE MRIs, and the standard approach of running `recon-all`, followed by `asegstats2table` is working fine for most regions. However, in some cases, the volumes are either zeroed out (e.g., for choroid plexus) or missing altogether (e.g., for habenula), and I am wondering what is the recommended approach to calculate volumes in these cases. Should I create a new segmentation volume manually on top of fsaverage that is aligned to my subject MRIs and run `mri_segstats`, or should I use `mri_synthseg`? Adding FreeSurfer and computer info in case it is helpful: * FreeSurfer version: `freesurfer-linux-centos7_x86_64-8.2.0-20260314-d932c45` * Platform: CentOS Linux 7 (Core) Thank you in advance, Robin Parth Chholak, Ph.D. Clinical NeuroImaging Research Core National Institute on Alcohol Abuse and Alcoholism National Institutes of Health Phone: +1 (301) 594-7416

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FS 8.0.0 Symlink Bug: Continue With 8.0.0 or Switch to 8.1.0/8.2.0 After Manual Edits?
by Lubig, Andreas 13 Jul '26

13 Jul '26

External Email - Use Caution Hello, I am working with a longitudinal dataset that was initially processed entirely with FreeSurfer 8.0.0. The cross-sectional time points were manually edited and then rerun with FreeSurfer 8.0.0. The base subjects and longitudinal subjects were also created with 8.0.0. I am now at the stage where I may need to manually edit the base subjects and possibly the longitudinal subjects, and I am unsure which FreeSurfer version I should use for the remaining edits and reruns. My concern is the documented FreeSurfer 8.0.0 bug in which rerunning recon-all can turn mri/orig.mgz into a symbolic link to mri/nu.mgz, particularly after manual editing and rerunning the processing. As far as I can tell, this bug did not occur in my dataset. I checked all relevant directories recursively and found no orig.mgz symbolic links and no cases in which orig.mgz and nu.mgz were byte-for-byte identical. My questions are: 1. Since the cross-sectional subjects were already manually edited and rerun with FreeSurfer 8.0.0, should I continue using 8.0.0 for manual edits and reruns of the base and longitudinal subjects in order to keep the processing version consistent, while checking that the symbolic-link error does not occur? 2. Alternatively, since it would take too much time to do all the manual edits all over again, can I keep the existing cross-sectional subjects and switch to a newer FreeSurfer version for the base and longitudinal processing? 3. If I should switch, would you recommend FreeSurfer 8.1.0 or 8.2.0? 4. Would it be acceptable to keep the existing base subjects created with 8.0.0 and use FreeSurfer 8.1.0 or 8.2.0 only for editing and rerunning the base and longitudinal subjects? Or should I first recreate the base subjects with 8.1.0 or 8.2.0 and only then begin the manual editing? I also have a separate question about the longitudinal results. Is it expected or possible that: * the cross-sectional subject looks correct after editing and rerunning, * the base subject also looks correct, * but the corresponding longitudinal subject contains pial-surface errors that are not present in either the cross-sectional or base subject? The longitudinal subjects look worse than the edited and rerun cross-sectional subjects and also worse than the base subjects. The study period was about one year, with two to three MRI sessions per participant. I observed this both in adolescent participants with anorexia nervosa who gained weight over the one-year period (and in whom substantial brain volume changes would be expected), and in adolescent healthy controls (in whom normal developmental brain changes are also expected). Could it indicate that something went wrong during the creation of the longitudinal subjects? If so, what is the most likely cause? Thank you very much for your help! Best regards, Andreas

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