Freesurfer

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30076 discussions

infantFS surface stats file
by Fernanda Hansen P. de Moraes 04 Apr '22

04 Apr '22

External Email - Use Caution Dear Freesurfer experts, I am running the infantFS version for subjects under 1-year-old, and it seemed to run successfully, despite I can't find the surface stats file with the average cortical thickness. Is it usually at the stats directory? Thank you very much in advance, Fernanda Hansen P. de Moraes fernandahmoraes(a)gmail.com Doutoranda em Ciências Médicas | Instituto D'Or de Pesquisa e Ensino e metaBIO (IF-UFRJ)

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Re: [Freesurfer] Beta values
by Laura Willers de Souza 04 Apr '22

04 Apr '22

External Email - Use Caution Sure! The fsgd file looks like this: GroupDescriptorFile 1 Title cortisol_CSF Class Main Variables cortisol_CSF Input 011_S_0003_S9128 Main 2.397895273 Input 022_S_0004_S9233 Main 2.772588722 Input 011_S_0005_S9137 Main 3.044522438 Input 011_S_0008_S9196 Main 2.397895273 Input 011_S_0010_S8800 Main 2.151762203 ... (n=300) Best, Laura. --------- On 4/3/2022, Douglas N. Greve wrote: Can you send the fsgd file? On 4/1/2022, Laura Willers de Souza wrote: Hello FreeSurfer Developers, I'm extracting beta values from some analyzes and I would like to know if I'm extracting and interpreting these values correctly. To extract the beta values I used this command: mri_segstats --seg lh.cortisol_CSF.glmdir/cortisol_CSF_slope/perm.th20.neg.sig.ocn.mgh --i lh.cortisol_CSF.glmdir/beta.mgh --excludeid 0 --avgwf lh.cortisol_CSF.beta.clusters.dat The model consists of 1 group and 1 covariate. I used the contrasts for intercept and slope. The beta values extraction file contains 2 lines (image below). [cid:228fe1e8-abaa-4279-83ec-5c81c3fb6a37] * Would the first line be the beta value for the intercept and the second line for the slope? * Thus the glm equation for the 1st cluster would be: cortical thickness = 2.57 - 0.12X + n Is this correct?

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freeview crashes
by Ogier, Stephen E. (Assoc) 04 Apr '22

04 Apr '22

External Email - Use Caution Hi, I'm new to Freesurfer, and I'm running into a reoccurring crash issue when I use freeview. I'm following the instructions at https://secure-web.cisco.com/1-t_-_RERzWYk0fp1i5OBDudvWxzXiP-RYynl0RMyOIkHs… After I open freeview, if I use the mouse to manipulate the image, eventually the program crashes and I receive this error message. The instruction at 0x00007ffa0d9b3460 referenced memory at 0x0000000000000010. The memory could not be read. Click on OK to terminate the program I've received this kind of error multiple times. The addresses for the instruction varies, and the memory address has also been 0x0000000000000000. Has anyone else come across this problem? For reference, I'm running the FS_7_2_0_ubuntu_18_04_06 VM in VirtualBox 6.1 on a Windows 10 PC (Version 20H2, OS Build 19042.1586). Thanks, Stephen Ogier, PhD Postdoctoral Associate, Magnetic Imaging Group, Applied Physics Division National Institute of Standards and Technology

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surf2surf - FS-FAST z.nii.gz from fsaverage to fsaverage5
by stdp82＠virgilio.it 04 Apr '22

04 Apr '22

External Email - Use Caution Hi list, I have carefully assessed the guidelines by surf2surf --help, but I need for your help. I want transform the z.nii.gz, which I obtained from seed-based functional connectivity by FS-FAST, from the fsaverage to fsaverage5. I have run: mri_surf2surf --s fsavarege --hemi lh --sval-tal-xyz ../fc.Xseed.surf.lh/g1v0/intercept/z.nii.gz --trgsubject fsaverage5 --tval lh.zfsaverage5.nii.gz --tval-xyz ./fc.Xseed.surf.lh/g1v0/intercept/z.nii.gz is the FS-FAST output in fsaverage lh.zfsaverage5.nii.gz would be the FS-FAST output in fsaverage5 but this error occurs /Applications/freesurfer/subjects/subject_prova/fsavarege/surf/lh.sphere.regNo such file or directory Stefano

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Tracula Longitudinal Reproducibility
by Thorn, Kathryn 04 Apr '22

04 Apr '22

External Email - Use Caution Hello all, I am currently using the longitudinal implementation of Tracula with a dataset of five subjects each with two time points. All follow-up time points were acquired roughly three weeks after all baseline time points on a different scanner (when our lab upgraded from a Siemens TimTrio to a Prisma) but with an equivalent sequence. In the past, ROI analyses have resulted in similar ROI means between baseline and follow up scans - roughly a < 5% difference between baselines and follow ups. I was hoping for a similar range of differences between baseline and follow up whole-tract means with Tracula. I've looked at the genu, splenium, and left/right SLF 1; the % differences between baselines and follow ups are all over the place, ranging from ~25% to <1%. After looking at the data, my team believes this wide range of differences to possibly and/or partially be due to some of the tracts sampling CSF. The genu and the splenium in particular yielded very large % differences for us, so our thought is that masking out CSF should cause our % differences to go down. My question is this: Is there an elegant way to implement CSF masking with Tracula? I don't believe Tracula has the ability to do the CSF masking itself, but is there a best practice of when/how to mask out CSF that works best with Tracula? Thank you! Kayti Thorn (she/her) Database Specialist Medical University of South Carolina Department of Neurology Center for Biomedical Imaging 135 Cannon St. CS101 Charleston, SC 29425

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Inverse transform
by Aleksandra Szum-Jakubowska 04 Apr '22

04 Apr '22

External Email - Use Caution Dear Freesurfer Experts, I conduct the segmentations' examines using Freesurfer recon-all (for segmentation hippocampus and ventricles), SAMSEG (for ventricles) and using FSL FIRST (for hippocampus). Now I have a problem with compare the result (calculating overlap). For Freesurfer and FIRST I used T1 MRAGE image (dimentions 176x256x256). For Samseg I used T2 FLAIR images coregistered to T1 MPRAGE (dimentions 176x256x256) I have result from Freesurfer with dimensions 256x256x256 I have results from FSL First and SAMSEG with dimensions 176x256x256. It is important that all results are concerned other spaces, so I cannot calculate overlap using that results and I have to perform transformation to the same space. I tried doing this: mri_label2vol --seg aseg.mgz --temp rawavg.mgz --o aseg-in-rawavg.mgz --regheader aseg.mgz but my rawavg image has dimensions 176x256x174). But when I used brain.mgz or T1.mgz image, my results are moved. I have no idea how to perform the properly inverse transformation for getting segmentation results in originally T1 MPRAGE space. Could You give me some advice? Thanks a lot for your help. Best regards, Aleksandra [UMB_MUB] Niniejsza wiadomosc oraz jej zalaczniki moga zawierac informacje chronione prawem. Jesli Panstwo nie jestescie adresatem tej wiadomosci, prosimy poinformowac o tym fakcie nadawce i usunac ja wraz z zalacznikami. Kopiowanie i/lub przesylanie dalej informacji zawartych w tej wiadomosci przez osoby do tego nieuprawnione jest zabronione. The information in this e-mail may be legally privileged. It is intended solely for the addressee. Access to this e-mail by anyone else is unauthorised. If you are not the intended recipient, any disclosure, copying, distribution or any action taken or omitted to be taken in reliance on it, is prohibited and may be unlawful. Administratorem Panstwa danych osobowych jest Uniwersytet Medyczny w Bialymstoku. Informacja dotyczaca zasad przetwarzania Panstwa danych dostepna jest pod adresem: https://secure-web.cisco.com/1G7fVk0yj2NQ8lWF3RpIcAXswlnvuIC6QkNdtflc_gKuCw…

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Tkregister2 not opening GUI
by Isabelle Deschamps 04 Apr '22

04 Apr '22

External Email - Use Caution Good afternoon, I am trying to verify the registration and for some reason the GUI is not opening. I am using a Macbook Pro running macOS Montery with a 2.4 Gz Quad-Core Intel Core i5 I have Freesurfer version: maOS-7.2.0 I do not get an error when I run TKregister2 or TKregister_cmld This is the output that I get without the GUI opening No target volume specified, assuming FreeSurfer orig volume. target volume orig movable volume (null) reg file (null) LoadVol 0 ZeroCRAS 1 7.2.0 Diagnostic Level -1 % % % % % % % % avi2talxfm talairach.xfm --------------------- 1.00857 0.02020 -0.00990 -0.12365; -0.01789 1.03251 0.24795 -28.10577; 0.02556 -0.30660 1.20913 3.54973; 0.00000 0.00000 0.00000 1.00000; INFO: loading target /Volumes/RestingState/fMRI/fMRI/Freesurfer/S0010_FS/mri/orig.mgz Zeroing CRAS of target new xfm ----------------- 1.00857 0.02020 -0.00990 1.93629; -0.01789 1.03251 0.24795 -11.46406; 0.02556 -0.30660 1.20913 -50.28331; 0.00000 0.00000 0.00000 1.00000; --------------------- Ttarg: -------------------- -1.00000 0.00000 0.00000 128.00000; -0.00000 0.00000 1.00000 -128.00000; 0.00000 -1.00000 0.00000 128.00000; 0.00000 0.00000 0.00000 1.00000; INFO: loading movable /Applications/freesurfer/7.2.0/average/mni305.cor.mgz Tmov: -------------------- -1.00000 0.00000 0.00000 128.00000; 0.00000 0.00000 1.00000 -128.00000; 0.00000 -1.00000 0.00000 128.00000; 0.00000 0.00000 0.00000 1.00000; mkheaderreg = 0, float2int = 0 ---- Input registration matrix -------- 1.00857 0.02020 -0.00990 1.93629; -0.01789 1.03251 0.24795 -11.46406; 0.02556 -0.30660 1.20913 -50.28331; 0.00000 0.00000 0.00000 1.00000; Determinant 1.33659 subject = S0010_FS RegMat --------------------------- 1.00857 0.02020 -0.00990 1.93629; -0.01789 1.03251 0.24795 -11.46406; 0.02556 -0.30660 1.20913 -50.28331; 0.00000 0.00000 0.00000 1.00000; UnZeroing CRAS for fstal output xfm Any help would be greatly appreciated. Isabelle

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slice timing for multiband fMRI
by Laura Doll 04 Apr '22

04 Apr '22

External Email - Use Caution Hi everyone, We are currently piloting an fMRI measurement with multiband sequence on a 3T Siemens scanner to increase resolution, but I don't know how to do the slice timing correction: I assume, that I have to use a slicedelay file instead of the usual up/down/even/odd/siemens flags? But how do I know which slices were excited simultaneously? Our multiband acceleration factor is 2, if I got our MRI physicist correctly, GRAPPA acceleration is also 2, and we are using a TR of 2s. More details of the sequence are in the attached pdf (which is unfortunately in German). Looking forward to any suggestions. Best, Laura

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Questions regarding ROI creation for SPM based on FreeSurfer parcellation
by Falko Mecklenbrauck 04 Apr '22

04 Apr '22

External Email - Use Caution Dear FreeSurfer-Experts, I’m in need of your experience to help me with a decision in my current project: I want to use certain areas, that were identified by structural graph theoretical analyses based on the FreeSurfer parcellation and DTI data, as Regions of interest in SPM. We already have a script that helps with the transfer and creation of ROIs however it is still unclear what’s the best way to create the ROIs. Here are a few of my ideas and pros and cons regarding these: 1. Parcel the MNI T1 standard brain used in SPM with FreeSurfer and create the ROIs from the identified regions from that PRO: direct use of the standard space, that is later used in SPM’s group level analysis CON: SPM tends to be peculiar in giving information about their standard template, so I am unsure if the one I found in the spm12-folder is the correct one to use 2. Extract the ROIs of each participant individually and then use SPM to normalize and averaging/summing these PRO: Ending up in same space as the SPM analysis CON: identified regions are (at the moment) not individually identified, although they could be; normalization is difficult with just ROIs ALTERNATIVE: use FreeSurfer not on individual “raw” T1 images but on already normalized T1 images and then do the ROIs individually per participant. Probably, I am also forgetting another possibility. I am looking forward to hearing your ideas and comments. Thank you very much in advance, Best wishes, Falko

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Re: [Freesurfer] mri_vol2vol anatomical to functional
by Manenti, Giorgio 04 Apr '22

04 Apr '22

External Email - Use Caution I'm not sure I understand what you are saying or what the problem is. Can you provide the actual command line you are using, all the terminal output, and a picture that shows what the problem is? Hi Douglas, thank you for your time; I am trying to get the ribbon at functional space resolution (I need it to extract the white matter from my ROIs) Here I am copying the 2 commands (one using .reg file, the second using .lta) I am using, and the terminal terminal outputs. Attached you will also find 3 screenshots from freeview with 1) original ribbon 2) ribbon transformed in functional space using the .reg file and 3) ribbon transformed using the .lta file. (Please Note: I am using Matlab to integrate this analysis in the general pipeline, so the command are started by the s=system() function;) %%%%%%REG s=system(['mri_vol2vol --reg ' regpath ' --mov ' inputvol ' --targ ' funcTemp ' --o ' outputvol ]); regio_read_register: loading lta Matrix from regfile: 0.99982 -0.01069 -0.01533 -0.11505; 0.01423 -0.09676 0.99521 -0.84297; 0.01212 0.99525 0.09659 -5.72961; 0.00000 0.00000 0.00000 1.00000; movvol Anatomy_Processed/hum_15477.long.long002/mri/lh.ribbon.mgz targvol FSfast_struc/all_sub/f02_Sess03/bold/ecc_lh/conjunction_pe/v1_trai_vol.nii outvol Anatomy_Processed/hum_15477.long.long002/mri/lh.ribbon_func.mgz regfile FSfast_struc/all_sub/f02_Sess03/bold/register.dof6.lta invert 0 tal 0 talres 2 regheader 0 noresample 0 interp trilinear (1) precision float (3) Gdiag_no -1 Synth 0 SynthSeed 1649422337 Final tkRAS-to-tkRAS Matrix is: 0.99982 -0.01069 -0.01533 -0.11505; 0.01423 -0.09676 0.99521 -0.84297; 0.01212 0.99525 0.09659 -5.72961; 0.00000 0.00000 0.00000 1.00000; Vox2Vox Matrix is: 2.01888 -0.03096 0.02351 23.93213; 0.02447 0.19504 -2.18955 197.85437; -0.02873 -2.00955 -0.21287 240.49161; 0.00000 0.00000 0.00000 1.00000; Resampling Output registration matrix is identity mri_vol2vol done %%%%%%LTA s=system(['mri_vol2vol --lta ' ltapath ' --mov ' inputvol ' --targ ' funcTemp ' --o ' outputvol ]); Matrix from LTA: 0.99983 -0.01069 -0.01533 -0.11505; 0.01423 -0.09676 0.99521 -0.84293; 0.01212 0.99525 0.09659 -5.72960; 0.00000 0.00000 0.00000 1.00000; Anatomy_Processed/hum_15477.long.long002/mri/lh.ribbon.mgz FSfast_struc/all_sub/f02_Sess03/bold/ecc_lh/conjunction_pe/v1_trai_vol.nii INFO: src volume info differs from the one stored in lta. gets modified now. volume geometry: extent : (256, 256, 256) voxel : ( 1.0000, 1.0000, 1.0000) x_(ras) : (-1.0000, -0.0000, -0.0000) y_(ras) : ( 0.0000, 0.0000, -1.0000) z_(ras) : (-0.0000, 1.0000, 0.0000) c_(ras) : ( 0.2540, 9.2232, 8.1562) file : Anatomy_Processed/hum_15477.long.long002/mri/lh.ribbon.mgz volume geometry: extent : (104, 104, 69) voxel : ( 2.0192, 2.0192, 2.2000) x_(ras) : (-0.9995, -0.0137, 0.0296) y_(ras) : ( 0.0126, -0.9991, -0.0397) z_(ras) : ( 0.0301, -0.0393, 0.9988) c_(ras) : ( 1.5530, 16.4346, 14.9788) file : bold/template.nii.gz INFO: dst volume info differs from the one stored in lta. gets modified now. volume geometry: extent : (104, 104, 69) voxel : ( 2.0192, 2.0192, 2.2000) x_(ras) : (-0.9995, -0.0137, 0.0296) y_(ras) : ( 0.0126, -0.9991, -0.0397) z_(ras) : ( 0.0301, -0.0393, 0.9988) c_(ras) : ( 1.5530, 16.4345, 14.9788) file : FSfast_struc/all_sub/f02_Sess03/bold/ecc_lh/conjunction_pe/v1_trai_vol.nii volume geometry: extent : (256, 256, 256) voxel : ( 1.0000, 1.0000, 1.0000) x_(ras) : (-1.0000, -0.0000, -0.0000) y_(ras) : ( 0.0000, 0.0000, -1.0000) z_(ras) : (-0.0000, 1.0000, 0.0000) c_(ras) : ( 0.2540, 9.2232, 8.1562) file : Anatomy_Processed/hum_15496.long.long002/mri/orig.mgz movvol Anatomy_Processed/hum_15477.long.long002/mri/lh.ribbon.mgz targvol FSfast_struc/all_sub/f02_Sess03/bold/ecc_lh/conjunction_pe/v1_trai_vol.nii outvol Anatomy_Processed/hum_15477.long.long002/mri/lh.ribbon_func.mgz regfile FSfast_struc/all_sub/f02_Sess03/bold/register.dof6.lta invert 0 tal 0 talres 2 regheader 0 noresample 0 interp trilinear (1) precision float (3) Gdiag_no -1 Synth 0 SynthSeed 1649445621 Final tkRAS-to-tkRAS Matrix is: 0.99828 0.04446 -0.03809 2.43217; 0.03729 0.01869 0.99913 9.13850; -0.04513 0.99884 -0.01700 12.13850; 0.00000 0.00000 0.00000 1.00000; Vox2Vox Matrix is: 2.01577 -0.07692 -0.09781 28.12225; -0.09113 -0.03433 -2.19744 198.19705; -0.07530 -2.01747 0.04112 244.54424; 0.00000 0.00000 0.00000 1.00000; Resampling Output registration matrix is identity mri_vol2vol done Many thanks again, Best Giorgio

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