Freesurfer

freesurfer@nmr.mgh.harvard.edu

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30070 discussions

Confirming FSGD Format and Contrasts
by Olivier Brown 27 Nov '22

27 Nov '22

External Email - Use Caution Dear FreeSurfer experts, I would like to confirm my FSGD file format and mtx contrasts prior to continuing with my analyses. Here is some background information: I have two groups (treatment, control) and would like to determine whether our quantitative scale, CDRISC, is associated with thickness within each group. I would like to control for sex, handedness, and age. Seeing as sex and handedness are categorical, I entered them as Classes instead of variables (Controlleftmale was not included, as no participant fell in that group). GroupDescriptorFile 1 Title CDRISC Class Controlrightfemale Class Controlleftfemale Class Treatrightfemale Class Treatleftfemale Class Controlrightmale Class Treatrightmale Class Treatrightmale Variables CDRISC_TREATMENT CDRISC_CONTROL age Input sub-1 Controlrightfemale 0 19 10.66 Input sub-2 Controlleftfemale 0 26 14 Input sub-3 Treatrightmale 35 0 14.02 Input sub-4 Treatleftmale 35 0 10.16 [...] My contrasts (DOSS) are as follows: [Nregressors = Nclasses + Nvariables Nregressors = 7 + 3 Nregressors = 10] Treatment CDRISC slope = 0 0 0 0 0 0 0 1 0 0 Control CDRISC slope = 0 0 0 0 0 0 0 0 1 0 Are there any glaring issues with this model? The only extra step of consideration here is that I have yet to demean the data. Any guidance is appreciated. Warm regards, Olivier Brown

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R: SAMSEG Lesion images not written
by Cerri, Stefano 27 Nov '22

27 Nov '22

Great! You can use the command "samseg" with the flag "--recon" instead of "run_samseg". This will first run SAMSEG to obtain a whole-brain segmentation, then recon-all will use this segmentation to perform surface analysis and cortical parcellation -- instead of using ASEG segmentation. Look at the help function for more information. Stefano ________________________________ Da: Giulio Siracusano <giuliosiracusano(a)gmail.com> Inviato: domenica 27 novembre 2022 10:07 A: Cerri, Stefano <SCERRI(a)mgh.harvard.edu> Cc: freesurfer(a)nmr.mgh.harvard.edu <freesurfer(a)nmr.mgh.harvard.edu> Oggetto: Re: [Freesurfer] SAMSEG Lesion images not written External Email - Use Caution Hi Stefano, I've got this thanks. I simply use freeview and ingest region-specific .mgz files. I just wanted to understand one thing. I realize that using SAMSEG or ASEG it is possible to obtain subcortical segmentation (44 parameters are visualized, representing different regions). I realized that fusiform gyrus, middle temporal and entorhinal cortex volumes cannot be derived using one of the above mentioned methods. I just wanted to know if is there any way to achieve cortical parcellation without using ASEG? Or, in alternative, is there a way to estimate fusiform gyrus, middle temporal and entorhinal cortex volumes from the variables obtained in samseg.stats? Hope to be clear Giulio Siracusano On Sun, 27 Nov 2022 at 14:22, Cerri, Stefano <SCERRI(a)mgh.harvard.edu<mailto:SCERRI@mgh.harvard.edu>> wrote: Hi Giulio, I'm not sure I understand what your goal is. Are you just trying to visualize specific brain structures over your input image? Are you interested in segmentation maps or binary segmentations? If you want to visualize segmentation maps, you can just use Freeview and load the specific structure file(s). Note that these segmentation maps are 1) not binary, i.e., they have values *between* 0 and 1, and 2) they are in the same space as your input image. If you want to visualize binary segmentation for specific structures you can do this in Freeview. You load your segmentation (seg.mgz) as a lookup table and select only the label values that you're interested in. Hope it helps, Stefano ________________________________ Da: Giulio Siracusano <giuliosiracusano(a)gmail.com<mailto:giuliosiracusano@gmail.com>> Inviato: domenica 27 novembre 2022 04:01 A: Cerri, Stefano <SCERRI(a)mgh.harvard.edu<mailto:SCERRI@mgh.harvard.edu>>; freesurfer(a)nmr.mgh.harvard.edu<mailto:freesurfer@nmr.mgh.harvard.edu> <freesurfer(a)nmr.mgh.harvard.edu<mailto:freesurfer@nmr.mgh.harvard.edu>> Oggetto: Re: [Freesurfer] SAMSEG Lesion images not written External Email - Use Caution Hi Stefano, I'd like to ask you a question wrt SAMSEG. I'd like to extract segmentation maps using SAMSEG, and I know already that we have to use '--save-posteriors' option when running the command. They will be saved in the samseg output directory under the "posteriors" folder. How is it possible, starting from these binary segmentation maps, creating multiple images of the brain where a given (segmentated) region is highlighed? In order to do that, you have to multiply a given reference brain images -over- each segmentation map (which is a binary matrix with 0's and 1's). What is the reference brain image all these segmentation maps are related to? I hope to be clear enough Best regards Giulio Siracusano 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 Mass General Brigham Compliance HelpLine at https://www.massgeneralbrigham.org/complianceline<https://secure-web.cisco.com/1maz9AvYDfMlSPw4n3XIzXHlH00MqWKYxfe-RJHrZ_up6-…> .

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R: SAMSEG Lesion images not written
by Cerri, Stefano 27 Nov '22

27 Nov '22

Hi Giulio, I'm not sure I understand what your goal is. Are you just trying to visualize specific brain structures over your input image? Are you interested in segmentation maps or binary segmentations? If you want to visualize segmentation maps, you can just use Freeview and load the specific structure file(s). Note that these segmentation maps are 1) not binary, i.e., they have values *between* 0 and 1, and 2) they are in the same space as your input image. If you want to visualize binary segmentation for specific structures you can do this in Freeview. You load your segmentation (seg.mgz) as a lookup table and select only the label values that you're interested in. Hope it helps, Stefano ________________________________ Da: Giulio Siracusano <giuliosiracusano(a)gmail.com> Inviato: domenica 27 novembre 2022 04:01 A: Cerri, Stefano <SCERRI(a)mgh.harvard.edu>; freesurfer(a)nmr.mgh.harvard.edu <freesurfer(a)nmr.mgh.harvard.edu> Oggetto: Re: [Freesurfer] SAMSEG Lesion images not written External Email - Use Caution Hi Stefano, I'd like to ask you a question wrt SAMSEG. I'd like to extract segmentation maps using SAMSEG, and I know already that we have to use '--save-posteriors' option when running the command. They will be saved in the samseg output directory under the "posteriors" folder. How is it possible, starting from these binary segmentation maps, creating multiple images of the brain where a given (segmentated) region is highlighed? In order to do that, you have to multiply a given reference brain images -over- each segmentation map (which is a binary matrix with 0's and 1's). What is the reference brain image all these segmentation maps are related to? I hope to be clear enough Best regards Giulio Siracusano

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Ubuntu 7z Password Requst
by RW :D 25 Nov '22

25 Nov '22

External Email - Use Caution To Whom It May Concern: I am requesting the password for the FS_7_2_0_ubuntu_18_04_06.ova.7z file so that I can extract the .ova file. I would really appreciate it if you could send it to me! Thank you so much! Sincerely,Rebecca Wu -

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FS_7_2_0_Ubuntu_18_04_06.ova.7z password
by Marcel Heers 24 Nov '22

24 Nov '22

External Email - Use Caution Can you please share the password for the above mentioned VirtualBox with me? Thanks in advance! Marcel

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Permission denied error
by Adam Tartaglia 23 Nov '22

23 Nov '22

External Email - Use Caution Hello, Immediately after running recon-all, I get an error that says cannot create directory, permission denied. I am not sure as to why this is happening. My license is in the correct location. Thank you for your time, - Adam

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Semi-automatic tool for QC of 41 TRACULA paths?
by Blujus, Jenna 23 Nov '22

23 Nov '22

External Email - Use Caution Hi all, I recently ran the longitudinal TRACULA pipeline in a large dataset (>600 participants) using Freesurfer v7.3.2. Each participant in this dataset has two time points of data. I've finished running trac-all -path, so each dataset has 42 reconstructed WM tracts. I see in the tutorial that visual QC is recommended to check path outputs for partial reconstruction errors. Given our large dataset (1200 scans x 42 tracts), I was wondering what QC procedures you would recommend. I know that visual inspection is the gold standard, but are there any automatic or semi-automatic procedures you would recommend? Thank you, Jenna

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How to set original orientation to be sagittal view?
by Haiyun Chen 22 Nov '22

22 Nov '22

External Email - Use Caution Hello Freesurfer Experts, How can we set the original orientation of an image file such that when the image is opened in a different application the original orientation is a sagittal viewport? For the file aseg.mgz in the below directory based on your tutorial, could you please tell a specific command to convert aseg.mgz to a file with sagittal viewport as the original orientation? tutorial_data_20190918_1558/practice_with_data/Subj001/mri/aseg.mgz Thank you in advance! Best regards Haiyun

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infant_recon_all surface correction
by Laura Mazzocchi 22 Nov '22

22 Nov '22

External Email - Use Caution Dear Experts, I am working with FreeSurfer infant_recon_all and I need to correct the pial surface for most of the analyzed subjects. I would like to implement this correction by fixing the intensity normalization using control points, as well as for the adult subjects with tkmedit, but I can not understand if it is then possible to re-run the infant_recon_all pipeline (or how) after the cp definition, since it seems to me that it does not exist the possibility to add -autorecon2-cp and -autorecon3 flags to infant_recon_all, like with the pipeline for adults. So, I am asking if you have some suggestion to do that. I have already tried to normalize the intensity with flag --intnormFSL, specific for infant_recon_all. The result is better but not the best. Is there any other possibility? For example: - to launch mri_nu_correct.mni --i $infile --o $nufile Then, should I add the --masked flag at the infant_recon_all command by passing $nufile as input? Which is the difference between this one and the --intnormFSL option? - Is there something similar to the adult -autorecon2-cp also for infants? - Do you think that the application of AntsN4BiasFieldCorrectionFs is a good idea? And what about the possibility of applying newborn FLAIR sequence to the Bias Field corrected images? - Could it be better to create my own atlas and to use that to obtain a better segmentation? Thank you very much for any kind suggestion. Best Regards, Laura Mazzocchi --- La ricerca neurologica ha bisogno anche di te SOSTIENI LA FONDAZIONE MONDINO CON IL TUO 5 X MILLE http://secure-web.cisco.com/1OcBqU8Yy68wxtJrh1xuYaYanoYCq1G_wyTWR4VlJonLrJ1…

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Re: [Freesurfer] Issue with rotation during longitudinal base creation
by Huang, Yujing 22 Nov '22

22 Nov '22

Hi Nathan, Can you confirm that the error was from mri_robust_template? Not sure what your command line options. I think these options ‘—inittp <>’, ‘--fixtp’, ‘—seed <>’ might help. Best, Yujing -------- Forwarded Message -------- Subject: [Freesurfer] Issue with rotation during longitudinal base creation Date: Wed, 12 Oct 2022 16:54:29 +0000 From: Nathan Kindred (PGR) <N.Kindred1(a)newcastle.ac.uk><mailto:N.Kindred1@newcastle.ac.uk> Reply-To: Freesurfer support list <freesurfer(a)nmr.mgh.harvard.edu><mailto:freesurfer@nmr.mgh.harvard.edu> To: freesurfer(a)nmr.mgh.harvard.edu<mailto:freesurfer@nmr.mgh.harvard.edu> <freesurfer(a)nmr.mgh.harvard.edu><mailto:freesurfer@nmr.mgh.harvard.edu> External Email - Use Caution Hi, I have been processing longitudinal data using the longitudinal processing stream but for some subjects I am having getting this error when creating the base: Input rotation's max deviation from rotation is: 0.000258493 MyMatrix::RotationMean input(s) not rotation What would be the best way to fix this? Best, Nathan

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