Freesurfer

freesurfer@nmr.mgh.harvard.edu

6 participants
30055 discussions

mri_glmfit error：ill-conditioned matrix
by Chen Yang 22 Nov '24

22 Nov '24

External Email - Use Caution Dear FreeSurfer experts, I tried to examine the thickness differences between two groups after controlling for the age, gender, and mean thickness, while I got an error message below: ERROR: matrix is ill-conditioned or badly scaled, condno = 1e+08 Possible problem with experimental design: Check for duplicate entries and/or lack of range of continuous variables within a class. If you seek help with this problem, make sure to send: Your command line: mri_glmfit.bin --y glm/FB_demo_lh_CT/lh.FB_demo_lh_CT.thickness.10B.mgh --fsgd glm/FSGD_files/createFSGD/FB_demo_lh_CT/FB_demo_lh_CT.fsgd --C glm/FB_demo_lh_CT/PS-NP.mtx --C glm/FB_demo_lh_CT/NP-PS.mtx --surf 43kids lh --glmdir glm/FB_demo_lh_CT/lh.FB_demo_lh_CT.thickness.10B.glmdir The FSGD file (if using one) And the design matrix above Attempting to diagnose further SumSq: Min=1.258825 (col 10), Max=5.384785 (col 5) ... could not determine the cause of the problem I have searched this problem in the mail archive. I have done the normalization for all covariables (age and mean thickness). Sex and test condition are treated as class variables. So I have no idea about the cause of the error. Here I attached the FSGD file and the matrix. The contrast is 0.5, -0.5, 0.5, -0.5, 0,0,0,0,0,0,0,0. Can someone help me? Thank you! Best regards, Chen -- Chen Yang PhD Student Independent Research Group 'Milestones of Early Childhood Development' Max Planck Institute for Human Cognitive and Brain Sciences Email:yangc@cbs.mpg.de

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mri_synthseg CT segmentation error
by "PD Dr. Susanne Gellißen" 22 Nov '24

22 Nov '24

External Email - Use Caution Hi, When I segment brain CT images using mri_synthseg with the following command line: mri_synthseg — $file_to_segment —o $output — robust —ct —threads 10 —vol FS_vol.csv —qc FS_qc.csv I get segmentation errors concerning the cortex for many CCTs: e.g. some scattered patches of the contralateral right cortex are segmented/labeled as left cortex and vise versa. How can I avoid this error? I think the algorithm should be able to recognize the hemisphere and not scatter patches of left cortex within right cortex? When I use —parchment paper I in the same patients I get similar segmentation errors but different voxels that are segmented with errors. Ho can I improve the segmentation and get at least correct segmentation of the hemispheres? ------------------------------------- PD Dr. med. Susanne Gellißen Department of Diagnostic and Interventional Neuroradiology University Medical Center Hamburg-Eppendorf Martinistraße 52, 20246 Hamburg E-mail: s.siemonsen(a)uke.de -- _____________________________________________________________________ Universitätsklinikum Hamburg-Eppendorf; Körperschaft des öffentlichen Rechts; Gerichtsstand: Hamburg | http://secure-web.cisco.com/1gKbDYZ9Jses5iVoFPW3XeKg6fABwND3QyMrgP5zleSvECU… Vorstandsmitglieder: Prof. Dr. Christian Gerloff (Vorsitzender), Joachim Prölß, Prof. Dr. Blanche Schwappach-Pignataro, Corinna Wriedt _____________________________________________________________________

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Question About Longitudinal TRACULA Analysis
by De Giorgi, Sara 21 Nov '24

21 Nov '24

Dear all, I wanted to ask you a question about longitudinal TRACULA analysis. I'm analyzing a group of patients with different time points. In my configuration file, I used "affine registration from the individual T1 to the MNI T1 template with FLIRT and a correlation ratio cost" as the inter-subject registration method (set interreg = 1). However, I’m considering whether it might be better for my analysis to use "nonlinear registration from the individual FA map to a custom FA template with symmetric normalization from ANTs" (set interreg = 5). I would appreciate your thoughts on this. Thank you in advance. Best regards, Sara

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Longitudinal processing including infant data
by Hendrikse, Chanelle [cbuckle＠sun.ac.za] 21 Nov '24

21 Nov '24

External Email - Use Caution Good day I am writing to enquire regarding the best approach to process longitudinal data acquired across 3 time points. The time points are as follows: * Infants (2-4 weeks old) – only T2 data available for this time point * 2-year-olds – T1 data available * 6-year-olds – T1 data available The approach I’m considering: * run the T2 infant data through synthmorph to create T1 images and then run infant Freesurfer on the synthetic T1 images * run Freesurfer 7.1.1 on 2-year-old data * I have Freesurfer 7.1.1 output for the 6-year-old data * Run the Freesurfer longitudinal pipeline across the 3 time points My questions are: * I know it is highly recommended that the same Freesurfer version be used for longitudinal processing, but this may not be possible given that our dataset includes infant data. What would happen if I ran the normal Freesurfer 7.1.1 on the infant data? Would it be reliable? If not, would it at all be possible to combine the infant Freesurfer output with the version 7.1.1. output in the longitudinal pipeline? * I saw that the beta version of Freesurfer 8 is out and that it includes synthmorph etc. Would it be better to process all the data with this version of Freesurfer? * When do you expect the stable release of Freesurfer 8 to come out? Thank you in advance for your guidance. Kind regards, Chanelle The integrity and confidentiality of this email are governed by these terms. Disclaimer<https://secure-web.cisco.com/1mYiWbfWgJICTMnHZeNDAJNLUO9qWS8T1BhEmMF309NBCg…> Die integriteit en vertroulikheid van hierdie e-pos word deur die volgende bepalings bereël. Vrywaringsklousule<https://secure-web.cisco.com/1mYiWbfWgJICTMnHZeNDAJNLUO9qWS8T1BhEmMF309NBCg…>

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Longitudinal FS Processing
by Yingling, Michael 20 Nov '24

20 Nov '24

External Email - Use Caution Hello, I hope that I am sending this question to the right place. Please let me know if not. I need to do longitudinal FS processing for a study that originally had 3 timepoints (data was processed a couple of years ago using FS for these 3 timepoints). Part 2 of the study has begun, which consists of 1 additional timepoint. What would be the best approach for using FS to process the data at this new timepoint given that the data for the other 3 timepoints have already been processed? Do I need to be careful with using different versions of FS? Thank you! Michael Michael Yingling, MS Senior Statistical Data Analyst Washington University SOM Department of Psychiatry Healthy Mind Lab Phone: (573) 579-1412 ________________________________ 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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recon-all Segmentation Error
by Boa Sorte Silva, Narlon 20 Nov '24

20 Nov '24

Hi there, Hope all is well Is there any preprocessing or additional steps within FreeSurfer that could help with issues like the ones in the images attached (aside from manual edits)? Granted this is an example of a sample of older individuals with marked neurodegeneration. Nárlon Cássio Nárlon C Boa Sorte Silva, PhD (He, Him, His) Postdoctoral Fellow Centre for Aging SMART, Vancouver Coastal Health Research Institute Djavad Mowafaghian Centre for Brain Health, Vancouver Coastal Health Research Institute Department of Physical Therapy, University of British Columbia +15196944893 https://secure-web.cisco.com/1WOyPTiy1S37KSd-TKeW2x9b9p4Iz3oChJj2C73O4_E4Rm… https://secure-web.cisco.com/11fPHF_NbaiAS9OznZllbCbArfM8-LaAlHeQDjv3l-NN6e… External Email - Use Caution

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mri_vol2surf error: GM estimation couldn't find enough samples
by Lee, Hansol 20 Nov '24

20 Nov '24

Dear FreeSurfer developers, I am attempting to use “mri_vol2surf” command to project output from diffusion MRI models (e.g., DTI) onto the cortical surface. The registration between the diffusion MRI and anatomical space was performed using “bbregister”, and the projection works well for different --projfrac values (e.g., 0 to 1 from the white matter surface). However, I encountered issues when attempting to use the “—projopt” option to account for partial volume effects. Specifically, I received the following errors: “reading gm volume fraction from /autofs/space/allegro_002/users/hlee/SANDI/pvf/Tract_HC_001_07222016/pvf.gm.mgz reading wm volume fraction from /autofs/space/allegro_002/users/hlee/SANDI/pvf/Tract_HC_001_07222016/pvf.wm.mgz reading csf volume fraction from /autofs/space/allegro_002/users/hlee/SANDI/pvf/Tract_HC_001_07222016/pvf.csf.mgz error: No such file or directory error: GM estimation at vno 0 couldn't find enough samples error: No such file or directory error: GM estimation at vno 1 couldn't find enough samples error: No such file or directory error: GM estimation at vno 2 couldn't find enough samples error: No such file or directory error: GM estimation at vno 3 couldn't find enough samples error: No such file or directory error: GM estimation at vno 4 couldn't find enough samples error: No such file or directory error: GM estimation at vno 5 couldn't find enough samples error: No such file or directory” In the directory, I already have “pvf.gm.mgz”, “pvf.wm.mgz”, and “pvf.csf.mgz” files. I searched the archive and found a similar error reported in this thread: https://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg72784.html I would greatly appreciate any insights or suggestions to resolve this issue. Thank you in advance for your help! Best regards, Hansol Lee

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Help with mri_vol2surf incorrect surface generation
by Pandey, Shraddha 20 Nov '24

20 Nov '24

External Email - Use Caution We are experiencing issues with `mri_vol2surf` generating an incorrect surface for the `Paramagnetic.nii` volume. Although the registration file (`volume_transform.dat`), created using `bbregister`, appears accurate, the output surface file (`Paramagneticsurface.mgh`) does not look correct. Specifically, some voxel values in the cortical areas are incorrectly predicted as zero. Command: ```bash input_volume=Paramagnetic.nii output_surface=Paramagneticsurface.mgh output_reg_file=volume_transform.dat mri_vol2surf --mov "$input_volume" --reg "$output_reg_file" --hemi lh --projfrac 0.2 --o "$output_surface" ``` Any guidance on resolving this issue with the surface generation would be greatly appreciated.

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mri_coreg error: could not open brainmask.mgz file to register PET image with anatomical
by Lai, Ian M. 20 Nov '24

20 Nov '24

External Email - Use Caution Trying to run this command: mri_coreg --s 002_S_0413_MPRAGE_SENSE2_2011-06-16_12_36_58.0_I240808_MPRAGE_SENSE2_SENSE_I240808_20110616121849_501 --mov 002_S_0413_MPRAGE_SENSE2_2011-06-16_12_36_58.0_I240808_MPRAGE_SENSE2_SENSE_I240808_20110616121849_501/pet/template.nii.gz --reg 002_S_0413_MPRAGE_SENSE2_2011-06-16_12_36_58.0_I240808_MPRAGE_SENSE2_SENSE_I240808_20110616121849_501/pet/template.reg.lta Receiving this output and error: $Id: mri_coreg.c,v 1.27 2016/04/30 15:11:49 greve Exp $ cwd /blue/babajani.a/SharedFolder_SDT_Fall24/MRI_FreeSurfer_Outputs/ADNI_FreeSurferResults/002_S_0413/MPRAGE_SENSE2/2011-06-16_12_36_58.0/I240808 cmdline mri_coreg --s 002_S_0413_MPRAGE_SENSE2_2011-06-16_12_36_58.0_I240808_MPRAGE_SENSE2_SENSE_I240808_20110616121849_501 --mov 002_S_0413_MPRAGE_SENSE2_2011-06-16_12_36_58.0_I240808_MPRAGE_SENSE2_SENSE_I240808_20110616121849_501/pet/template.nii.gz --reg 002_S_0413_MPRAGE_SENSE2_2011-06-16_12_36_58.0_I240808_MPRAGE_SENSE2_SENSE_I240808_20110616121849_501/pet/template.reg.lta sysname Linux hostname login9.ufhpc machine x86_64 user ianlai dof 6 nsep 2 cras0 1 ftol 0.000000 linmintol 0.001000 bf 1 bflim 30.000000 bfnsamp 30 SmoothRef 0 SatPct 99.990000 MovOOB 0 optschema 1 Seed 53 Reading in mov 002_S_0413_MPRAGE_SENSE2_2011-06-16_12_36_58.0_I240808_MPRAGE_SENSE2_SENSE_I240808_20110616121849_501/pet/template.nii.gz Reading in ref /apps/freesurfer/7.4.1/subjects/002_S_0413_MPRAGE_SENSE2_2011-06-16_12_36_58.0_I240808_MPRAGE_SENSE2_SENSE_I240808_20110616121849_501/mri/brainmask.mgz error: mghRead(/apps/freesurfer/7.4.1/subjects/002_S_0413_MPRAGE_SENSE2_2011-06-16_12_36_58.0_I240808_MPRAGE_SENSE2_SENSE_I240808_20110616121849_501/mri/brainmask.mgz, -1): could not open file I am able to manually download the brainmask.mgz file from that directory and open it in MRIcroGL, wondering what could be the issue here? Also dealing with a separate issue where when doing mri_gtmpvc \ --i 002_S_0413_MPRAGE_SENSE2_2011-06 16_12_36_58.0_I240808_MPRAGE_SENSE2_SENSE_I240808_20110616121849_501/pet/002_S_0413.nii.gz \ --reg 002_S_0413_MPRAGE_SENSE2_2011-06-16_12_36_58.0_I240808_MPRAGE_SENSE2_SENSE_I240808_20110616121849_501/pet/template.reg.lta \ --psf 6 \ --seg 002_S_0413_MPRAGE_SENSE2_2011-06-16_12_36_58.0_I240808_MPRAGE_SENSE2_SENSE_I240808_20110616121849_501/mri/gtmseg.mgz \ --default-seg-merge \ --auto-mask 1 .01 \ --mgx .01 \ --km-ref 46 47 \ --km-hb 11 12 50 51 \ --no-rescale \ --o 002_S_0413_MPRAGE_SENSE2_2011-06-16_12_36_58.0_I240808_MPRAGE_SENSE2_SENSE_I240808_20110616121849_501/gtmpvc.kmref-46-47.kmhb-11-12-50-51-output, The output in the gtmstats file seems to be exactly the same when changing km-ref from 7 8 46 47 to 46 47, which I have also attached. Have never done this before so no idea if these values are in a range that seems reasonable or if it means we are providing it a blank file. Any help would be appreciated, Ian. 1) FreeSurfer version: freesurfer-linux-centos8_x86_64-7.4.1-20230613-7eb8460 2) recon-all.log: see attached

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How to interpret the vertex-wise area metric?
by Alex 20 Nov '24

20 Nov '24

External Email - Use Caution Dear FreeSurfer experts, I have a question about the interpretation of the vertex-wise area metric. For instance, if Vertex A had a larger area than Vertex B, then what's the difference between Vertex A and Vertex B biologically?  Based on my simple (probably wrong) understanding of the surface reconstruction process, the initial surface was created based on the GM-WM boundary voxels, in which the face of a voxel was divided into two triangles and the area of the triangles was equal. But after the refinement of the initial surface, the triangle area was not uniform any more. So what factors may explain the expansion or contraction of the surface triangles? I believe these factors may help me understand the vertex-wise area metric. Maybe I should treat the vertex and the triangles around it as a whole, which is the unit of comparison. For instance, the Vertex A having a larger area means the area of triangels around Vertex A is larger. This kind of interpretation would make the comparsion between Vertex A and B biologically meaningless. From another perspective, in the voxel-based morphometry (VBM), the voxel size is fixed and the volume is the proportion or probability of GM (or other tissue types) in the voxel. In the surface case, if the triangle size is kept fixed, the area is proportial to the number of triangles, which is conceptually similar to the VBM approach. Why FreeSurfer did not choose this kind of approach? Sorry if this question is not reasonable, as I did not have a strong technical background. Best, Yang Hu

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