Freesurfer

freesurfer@nmr.mgh.harvard.edu

30132 discussions

Extracting values from a single vertex
by Nillo, Ryan Michael R 07 Nov '18

07 Nov '18

External Email - Use Caution Hi FreeSurfer users, I want to extract thickness values at a single vertex. I searched on the support list and found an mris_convert command to use. However, the file I want to extract values from is a volume with multiple frames. When I try to use mris_convert on it, I only got the value at a vertex on the first frame. The goal is to set that vertex as a seed point and use the values as a regressor for glm. Is there a way to do this with FreeSurfer's commandline tools, or should I do this in Matlab? Mahalo, Ryan M Nillo Staff Research Associate I UCSF Department of Radiology and Biomedical Imaging

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applying the same edits to multiple scans
by Hanford, Lindsay C 07 Nov '18

07 Nov '18

Hello Freesurfer Experts, I am wondering whether it is possible to apply the same manual edits (removing GM/WM or adding CPs) to multiple scans. I have a dataset with ~100 scans per subject acquired in quick succession and, interestingly, Freesurfer appears to have the same issue in almost all of the scans (I guess that speaks to the reliability!). In this case, a small region of the optic nerve is being included as GM (and occasionally WM) so I am wondering whether I can reduce my time with manual edits by either (1) applying the same edits to multiple images, or (2) in this case, applying a more constrained mask to remove the possibility of including optic nerve within the brainmask. Thank you in advance, Lindsay

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GLM
by 郑凤莲 07 Nov '18

07 Nov '18

External Email - Use Caution Hi experts, I am using FS 6.0 for analyzing the cortical thickness difference between 3 groups: patient1, patient2 and control. In DODS model, I need to creat 2 files, FSDG and mtx file. And we have 3 variables: age, gender and cortical thickness. 1. The FSDG file is: GroupDescriptorFile 1 Title Tutorial Class patient1-male Class patient1-female Class patient2-male Class patient2-female Class control-male Class control-female Variables age Input subject1 patient1-female 20 Input subject2 patient1-male 33 Input subject3 patient2-female 40 Input subject4 patient2-male 50 Input subject5 control-male 30 Input subject6 control-female 35 And there is another way: GroupDescriptorFile 1 Title Tutorial Class patient1 Class patient2 Class control Variables sex age Input subject1 patient1 1 20 Input subject2 patient1 2 33 Input subject3 patient2 1 40 Input subject4 patient2 2 50 Input subject5 control 2 30 Input subject6 control 1 35 What I want to confirm is that if I want to adjust for sex and age, which one is right? Another question is that is there any way to get the multiple comparisons between groups simultaneously? I am looking forward to your reply. Thanks very much. Sincerely, Zheng

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aparcstats2table --parcs-from-file trouble
by Figueiro Longo, Maria Gabriela 07 Nov '18

07 Nov '18

Hi, I extracted some volumes using mri_annotation2lable --> mri_aparc2aseg --> mri_segstats <file>. Now I am trying to extract the summary table using aparcstats2table --parcs-from-file <file>, but every time an error message pops up: ERROR: cannot read <file> The stats files generated by the mri_segstats look correct (similar with the other files in the directory) and I can read the volumes of each individual. The last command that has an error is: aparcstats2table --qdec-long qdec.txt --hemi lh --meas volume --parcs-from-file <file> --tablefile volumes.txt I really appreciate any help! Thanks! Gabriela

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First level modelling in task-based fMRI data
by Zhi Li 07 Nov '18

07 Nov '18

External Email - Use Caution Hi FreeSurfer Experts, Now I am trying FS-FAST in analyzing task-based fMRI data. We have two runs for each participant. However, there were not enough events in some runs of some participants. Hence we'd like to concatenate the preprocessed images of two runs into one rather than model them separately. How can we combine the preprocessed surface and sub-cortical data of each run into one? In addition. can we use FreeSurfer or FS-FAST to analyse task-based functional connections, such as psychophysiological interactions analysis and dynamic causal modelling? Do you have any suggestions? Thank you and best wishes, Zhi

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Re: [Freesurfer] Myelinated cortical thickness ratio map
by Damien MARIE 07 Nov '18

07 Nov '18

External Email - Use Caution Hi Matt, Many thanks for your prompt reply, you are right. Any tips on how I could do that? Should I regress out cortical thickness from my myelin maps at the individual level, save the individual output myelin maps and run analyses on the latter? If yes how? That’s really important to me otherwise a reviewer could claim the myelin differences we detect might be supported by cortical thickness variations and not myelin… Thank you and best, Damien > Glasser, Matthew <https://www.mail-archive.com/search?l=freesurfer@nmr.mgh.harvard.edu&q=from…> Mon, 22 Oct 2018 12:57:43 -0700 <https://www.mail-archive.com/search?l=freesurfer@nmr.mgh.harvard.edu&q=date…> > > Regression would be better than division. > Matt. > > From: > <freesurfer-boun...(a)nmr.mgh.harvard.edu <http://nmr.mgh.harvard.edu/><mailto:freesurfer-boun...@nmr.mgh.harvard.edu <mailto:freesurfer-boun...@nmr.mgh.harvard.edu>>> > on behalf of Damien MARIE <damien.ma <http://damien.ma/>...(a)unige.ch <http://unige.ch/><mailto:damien.ma...@unige.ch <mailto:damien.ma...@unige.ch>>> > Reply-To: Freesurfer support list > <freesurfer(a)nmr.mgh.harvard.edu <mailto:freesurfer@nmr.mgh.harvard.edu><mailto:freesurfer@nmr.mgh.harvard.edu <mailto:freesurfer@nmr.mgh.harvard.edu>>> > Date: Monday, October 22, 2018 at 8:54 AM > To: "freesurfer(a)nmr.mgh.harvard.edu <mailto:freesurfer@nmr.mgh.harvard.edu><mailto:freesurfer@nmr.mgh.harvard.edu <mailto:freesurfer@nmr.mgh.harvard.edu>>" > <freesurfer(a)nmr.mgh.harvard.edu <mailto:freesurfer@nmr.mgh.harvard.edu><mailto:freesurfer@nmr.mgh.harvard.edu <mailto:freesurfer@nmr.mgh.harvard.edu>>> > Subject: [Freesurfer] Myelinated cortical thickness ratio map > > > External Email - Use Caution > > Dear experts, > > I am working with R1 maps that I project on the surface. The goal is to look at > intra-cortical myelin. > > I detect interesting effects between two groups. Now I would like to compute > myelinated cortical thickness ratio maps, in order to control for the effect of > cortical thickness variations occurring with gyrification. > > Here is a paper where they describe a way to compute those myelinated cortical > thickness ratio map with MIPAV and the MPI-CBS toolbox : > https://www.ncbi.nlm.nih.gov/pubmed/29321232 <https://www.ncbi.nlm.nih.gov/pubmed/29321232> > « The proportional thickness of the myelinated part of the cortex in relation > to its overall thickness (myelinated cortical thickness) was computed with a > fuzzy classification technique combining information about radial and > tangential fibers. « > > 1- Is it possible to do the same in FreeSurfer? > > 2- What about dividing my individual myelin maps by the individual cortical > thickness maps? Is it possible to do that in FreeSurfer? SPM ImCalc would do > the job in the volume but I don’t know how I could do that in FreeSurfer. > > Any comments / other suggestions are welcome. > > Thank you and best, > > Damien >

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help with subjects concatenation/dimension inconsistency error
by Barletta, Valeria 06 Nov '18

06 Nov '18

Dear FreeSurfers, I am trying to apply surface processes to concatenate my cohort, but for some subjects I am getting this error: mri_surf2surf --srcsubject Ctrl034_R01_07 --srchemi rh --srcsurfreg sphere.reg --trgsubject fsaverage --trghemi rh --trgsurfreg sphere.reg --tval /autofs/space/alicudi_002/users/mscat/users/valeria/2017_CME_MTR_PET/2017_MTR_PET/T1/allSubj/tmp.mris_preproc.61312/Ctrl034_R01_07.18.mgh --sval /autofs/space/alicudi_002/users/mscat/users/caterina/3T/recons_fsv5.3/Ctrl034_R01_07/surf/overlay/rh.T1_mp2rage_depth0.5_fwhm3.mgh --noreshape --no-cortex ERROR: dimension inconsistency in source data Number of surface vertices = 138446 Number of value vertices = 137970 Source registration surface changed to sphere.reg Target registration surface changed to sphere.reg srcsubject = Ctrl034_R01_07 srcval = /autofs/space/alicudi_002/users/mscat/users/caterina/3T/recons_fsv5.3/Ctrl034_R01_07/surf/overlay/rh.T1_mp2rage_depth0.5_fwhm3.mgh srctype = trgsubject = fsaverage trgval = /autofs/space/alicudi_002/users/mscat/users/valeria/2017_CME_MTR_PET/2017_MTR_PET/T1/allSubj/tmp.mris_preproc.61312/Ctrl034_R01_07.18.mgh trgtype = srcsurfreg = sphere.reg trgsurfreg = sphere.reg srchemi = rh trghemi = rh frame = 0 fwhm-in = 0 fwhm-out = 0 label-src = (null) label-trg = (null) OKToRevFaceOrder = 1 Reading source surface reg /autofs/space/alicudi_002/users/mscat/users/caterina/3T/recons_fsv5.3/Ctrl034_R01_07/surf/rh.sphere.reg Loading source data And the script running stops immediately after. I already tried to relaunch the -autorecon2 -autorecon3 command for those subjects, since we already had this kind of issue in the past, but it didn't work. Do you have any idea of what could be the problem? Thank you very much, Valeria

2 2

ICV normalization (longitudinal pipeline)
by Martin Juneja 06 Nov '18

06 Nov '18

External Email - Use Caution Hello FS experts, I am using longitudinal processing pipeline ( https://surfer.nmr.mgh.harvard.edu/fswiki/LongitudinalProcessing) to calculate the cortical volume (CV) over a course of treatment (two conditions: pre condition and post condition). In fact, I am interested in comparing normalized CV (NCV) i.e. raw CV/ ICV between pre- and post-condition. (1). Now, longitudinal pipeline assumes that there is no change in ICV so it gives me identical ICV for pre and post condition. That way, when I compared NCV between pre and post condition, it gives me differences at significant level of 0.16. (2). However, when I checked ICV (from cross-sectional pipeline i.e. each time-point separately) and compared between pre and post-conditions, ICV values are different. Its possible that these values could be different because of treatment (may be !). When I compared NCV between pre and post condition (calculated by dividing raw CV from longitudinal pipeline with ICV values form cross-sectional pipeline), it gives me significant differences at 0.02. Could you please share your thoughts on this i.e. (a) whether I can use approach 2 or (b) if I am using longitudinal pipeline, dividing raw CV from longitudinal pipeline and dividing by ICV calculated from cross-sectional is in correct way to do this analysis? Thanks.

2 1

Recon-all run error
by 1013364183 06 Nov '18

06 Nov '18

External Email - Use Caution Dear FS, When we run “recon-all” with a 5GB high-resolution image, core dumped appears when the mri_convert command is executed. The specific errors are as follows: /opt/el7/pkgs/freesurfer/freesurfer_6.0/bin/mri_convert: line 3: 29235 Aborted (core dumped) mri_convert.bin "$@" ERROR: converting to minc We want to know if our high resolution image is too large for freesurfer to handle, or our computer memory (64GB running memory) is limited. Thanks a lot in advance! yours sincerely, yu junjie

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İlt: Desikan Atlas in volume space
by ece ulug 06 Nov '18

06 Nov '18

External Email - Use Caution Dear Experts, I am very beginner in Freesurfer, and I want to use 'read_annotation' function but i don't know what is the next step. I added the Matlab screenshoot. Additionally; 'read_curv' function don't work in Matlab. I added it. Thanks in advance Ece

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