Freesurfer

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19 participants
30088 discussions

Lesion mask
by Aaron Tanenbaum 04 Jun '19

04 Jun '19

External Email - Use Caution I am working on a project where we are attempting to automate localization of white matter hyper intensities. So far it looks good. I was wondering is there a way to feeding this mask to FreeSurfer 6.0 to help improve of the parcellation and segmentation. Thank you

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IronTract tractography challenge now open
by Yendiki, Anastasia 04 Jun '19

04 Jun '19

Dear all - The IronTract tractography challenge is now open. For more information on challenge tasks, ranking criteria, and how to participate, please visit: https://irontract.mgh.harvard.edu There will be 2 winners: * Overall winner: The goal is to find the tractography method that achieves the highest accuracy possible regardless of diffusion sampling scheme. You can use the full set of b-values/directions as provided, or only those that work best for your method of choice. * HCP winner: The goal is to find the tractography method that is best suited for the 2-shell acquisition scheme that the 6500+ data sets of the lifespan and disease Human Connectome Project studies are being collected with. Are you a developer who wants to showcase the performance of your latest tractography method? Are you a data analyst who wants to see how the tools used for your lab's studies compare to other approaches? This is your chance! Results will be announced at the IronTract challenge session at MICCAI 2019. Participants will have further opportunities to participate in publications that will result from the challenge. The challenge will run on the QMENTA platform. To register and get your access codes for the platform, please visit: http://irontract.mgh.harvard.edu/register/ On behalf of the organizers, Anastasia Yendiki.

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How to get the difference between orig.mgz and original image
by chen 04 Jun '19

04 Jun '19

External Email - Use Caution Hi experts, I selected hippocampus and amygdala as ROIs to estimated the reliability of a well-controlled multi-site study. But, amygdala volume (generated by FreeSurfer) presented a relatively poor ICC scores between sites. The major sources of between-site variation might be related to field inhomogeneity and other issues idiosyncratic to individual each scanners. Due to this reason, i want to check my data to confirm the field inhomogeneity located in amydala area or not. How can i get the difference between the original image and the images after motion and NU intensity? I am looking forward to your suggests. Cheers, Jiachen

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Post-doc position for MRI-research on frontotemporal dementia available at Karolinska institute.
by Erik Lindberg 04 Jun '19

04 Jun '19

External Email - Use Caution Post-doc position for MRI-research on frontotemporal dementia available at Karolinska institute. We are looking for a Post-doc researcher for a 1-year scholarship (with a possibility for an extension to 2-year) at our section at the NVS-department at Karolinska institute. For further information see: https://ki.mynetworkglobal.com/se/what:job/jobID:273493/type:job/where:4/ap…

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Statistical questions re: mri_glmfit and Monte Carlo sim corrections
by Jee Su Suh 04 Jun '19

04 Jun '19

External Email - Use Caution Hello FreeSurfer community, I am struggling to explain a statistical inconsistency in vertex-wise GLM results I've obtained, corrected using the Monte Carlo simulations, the details of which are as follows: I have 181 subjects in Group 1, and 95 subjects in Group 2 (the control group), which are compared in a cross-sectional design controlling for age, sex and scanning site. Following correction for multiple comparisons (vertex-wise p < 0.0001, cwp = 0.05), there are no surviving clusters. Group 1 is further subdivided into three subgroups, Group 1A (n=64), 1B (n=42) and 1C (n=35). The same design above is applied, comparing each subgroup with the control group, ie. Group 1A vs Group 2, Group 1B vs Group 2, etc. These comparisons exhibit clusters which *do* survive the exact same correction procedure as above. The significant cluster pattern across these comparisons are similar, indicating that there is some common underlying pathophysiology in Group 1. The crux of the issue is that when all the subgroups are combined into Group 1 and compared with the same control group, these meaningful differences do not survive correction, even though one might expect that increasing the power would be helpful in actually seeing these differences. The uncorrected results of this comparison are still suggestive of the pattern that was observed in the significant subgroup results. My intuition so far is that it may have something to do with the pooled variance, since it depends on the smaller sample of the two compared groups. In the overall comparison, Group 1 sample size is twice as large as Group 2, whereas for the subgroup comparisons, this relationship is reversed (Group 2 N is much larger than subgroup Ns). I've also looked at the gammavar.mgh maps of the comparisons, and variance throughout the brain does increase as the subgroup N decreases. However, I do not know for sure how to extend this explanation to its conclusion, and was wondering if anyone might be able to provide some additional insight into how I can explain the above statistically. Please let me know if there is any other information you need. Thanks very much, JeeSu

1 0

4 optseq2 questions
by Katarina Bendtz 04 Jun '19

04 Jun '19

External Email - Use Caution Dear experts: I'm using the optseq2 version 2.15 2009/05/26. I have three questions: 1. How does the [PSDmin, PSDmax] relate to the jittered intertrial intervals? 2. I have stimuli of between 12 and 20 seconds, where the part of my stimulus that I want to measure is in the last 5 seconds or so. What should I put my dPSD window to? It's both a matter of that the signal starts later than the stimulus presentation, so I guess I would have a PSDmin of a couple of seconds, but how do I handle the variation in stimuli lengths? 3. As mentioned above I have quite a large variation between my stimuli. When I try to specify them individually (about 25) I always get that all schedules are ill-conditioned. Is this because such schedules are generally hard to optimize? 4. I quite often get that all schedules are ill-conditioned, but there is no information in the log file that tells me what is wrong. Example: ./optseq2 --ntp 1500 --tr 1.86 --psdwin 0 22.32 0.93 --nkeep 3 --nsearch 1000 --o test --ev control_trial_1 16.74 1 --ev control_trial_3 18.6 1 --ev control_trial_7 18.6 1 --ev test_trial_11 16.74 1 I get: NFO: searched 1000 iterations for 0.010556 hours INFO: 26.3158 iterations per second INFO: 1000/1000 schedules were ill-conditioned ERROR: all schedules found were ill-conditioned. This probably means that you need more scan time (ie, a greater number of time points) or fewer repetitions. (I'm running on a macOS Mojave version 10.14.3. ) But it's obviously not the ntp that is the problem since I put an extra long time there that cover the event durations by far. Is there any way I can troubleshoot more efficiently myself? The log file doesn't tell me anything. Very happy for any advice, All the best, Katarina Katarina Bendtz, Ph.D. (particle physics) Postdoctoral researcher in cognitive neuroscience Department of Psychology, Stockholm University

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FS recon-all issue "if: missing file name"
by Kavinash Loganathan 04 Jun '19

04 Jun '19

External Email - Use Caution Dear freesurfer, I am following the installation test as suggested ( http://surfer.nmr.mgh.harvard.edu/fswiki/DownloadAndInstall/) and am currently stuck at example 2. When I ran recon-all, I got the output: "if: missing file name". I noticed this has been brought up before, but no solution was provided. Any suggestions? Thank you. Kavinash

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Pial surface segmentation QC through recon-all
by Faezeh Vedaei 04 Jun '19

04 Jun '19

External Email - Use Caution Hello I just needed to get help from someone has experience working on correcting pial surface segmentation by recon-all. Based on FreeSurfer tutorial and some instructions I have found by googling I have found some clues that was helpful, but for the issue I have right now was not enough. As you know I need to make sure that there is no dura or blood flow included in pial surface (cortex), so need to do editing by removing extra voxels. For some of our subject's data, there are some spots or areas obviously has no barrier between dura and cortex, and in my eyes it seems dura in included in the cortex (or cortex is extended to the dura) which needs correction. But I was wondering if I want to remove them, that would be so time-consuming and hard to check and edit every spot and slice, as these are shown a lot on many spots. So do you recommend me to do editing on these areas or forget about? I really appreciate that if you clarify me about this process specifically dura removing correction. Bests Faeze

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Re: [Freesurfer] Freesurfer V6 installation: ubuntu virtual machine
by fsbuild 03 Jun '19

03 Jun '19

External Email - Use Caution Hello Steve, We have run the freesurfer 6.0.0 release on Ubuntu 16 and 18 which should also work in a VM. You may have to install some packages in order to run freesurfer, especially for the freeview program which uses various graphics packages, etc.  After downloading the freesurfer 6.0.0 binaries from, https://surfer.nmr.mgh.harvard.edu/pub/dist/freesurfer/6.0.0/freesurfer-Lin… - I would first try to run the freeview binary as that is a good test to help determine what packages may be missing. I needed to both build and run freesurfer on Ubuntu, so I will list below the packages I installed for both purposes.  You should not need for example the gcc compiler packages just to run the 6.0.0 release binaries, but I have not tried to identify a set of packages to only run the binaries. You will likely also need sudo privileges to install packages. - R.      $ sudo apt-get install build-essential     $ sudo apt-get install libgl1-mesa-dev freeglut3-dev mesa-common-dev     $ sudo apt-get install libblas-dev liblapack-dev     $ sudo apt-get install ocl-icd-opencl-dev     $ sudo apt-get install libxmu-dev libxi-dev     $ sudo apt-get install libopencv-dev      Ubuntu 16:  $ sudo apt-get install gcc-4.9 g++-4.9 gfortran-4.9     Ubuntu 18:  $ sudo apt-get install gcc-4.8 g++-4.8 gfortran-4.8     $ sudo apt-get install xorg xorg-dev libx11-dev     $ sudo apt-get install tcl tcl-dev tk tk-dev     $ sudo apt-get install qt5-default qtcreator     $ sudo apt-get install libqt5x11extras5-dev     $ sudo apt-get install git-annex      $ sudo apt-get install python3-dev     … you will need a libpng, which I got from the archives,     http://se.archive.ubuntu.com/ubuntu/pool/main/libp/libpng/libpng12-0_1.2.54-1ubuntu1_amd64.deb     $ curl -O  http://se.archive.ubuntu.com/ubuntu/pool/main/libp/libpng/libpng12-0_1.2.54-1ubuntu1_amd64..deb    - then install the gdebi tool,      $ sudo  apt install gdebi     - change directories to where you downloaded the libpng12 package, and use gdebi to install it,     $ sudo  gdebi  libpng12-0_1.2.54-1ubuntu1_amd64.deb On May 31, 2019, at 02:57, Steve Petersen <marfneuro(a)GMAIL.COM> wrote:        External Email - Use Caution        Dear Freesurfer experts, Just a simple question, is possible to install the Freesurfer (Version 6) in a virtual machine of ubuntu?Thanks in advance,Best regards,Steve_______________________________________________Freesurfer mailing listFreesurfer@nmr.mgh.harvard.eduhttps://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer

2 1

Problem with lme_mass_fit_vw
by Hua, Jessica 03 Jun '19

03 Jun '19

External Email - Use Caution Dear FreeSurfer Experts, Just reposting this since I did not see it on the forum. I am trying to run longitudinal gyrification analyses following the FreeSurfer Linear Mixed Effects Models instructions, and I ran into a problem using lme_mass_fit_vw. I have 49 participants, and each participant has 2 timepoints. My model is: Yij = ß1 + ß2*tij +ß3*adjBACi + ß4*adjBACi *tij + ß5*sexi + ß6*ICVi + b1i + b2i*tij + eij lhcortex 1x149955 uint32 lhsphere 1x1 struct M 98x4 double mri 1x1 struct ni 49x1 double Qdec 99x4 cell sID 98x1 cell X 98x6 double Y 98x163842 double X Column 1 = column of 1s X Column 2 = column of alternating 0s and 1s (corresponding to either time 1 or time 2) X Column 3 = adjBAC X Column 4 = adjBAC * column 2 X Column 5 = participant's sex X Column 6 = participant's ICV After following the steps in the FreeSurfer instructions, I ran this code: lhstats = lme_mass_fit_vw(X,[1],Y,ni,lhcortex); And I got the following errors: Error using parfor_progress (line 17) Do you have write permissions for /Applications/freesurfer/matlab/lme/mass_univariate? Error in lme_mass_fit (line 155) fn = parfor_progress('init',nv); Error in lme_mass_fit_vw (line 73) [stats1,st1] = lme_mass_fit(X,[],Xrows,Zcols,Y,ni,prs,e); Do you know what I am doing wrong? I am using Matlab R2018b (with parallel computing) and FreeSurfer v.6.0. Please let me know if you need me to provide you with any additional information. Thank you! Jessica Hua

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