Freesurfer June 2019

freesurfer@nmr.mgh.harvard.edu

82 participants
138 discussions

how to obtain a mean .mgh file
by Barletta, Valeria 04 Jun '19

04 Jun '19

Dear Freesurfers, Is there a way to turn N .mgh files in to a single output .mgh file in which each vertex is the mean of the corresponding vertices in my input files? For example, input lh.Ctrl029.fsaverage.mgh , lh.Ctrl030.fsaverage.mgh , lh.Ctrl031.fsaverage.mgh , lh.Ctrl032.fsaverage.mgh >>> output lh.mean.fsaverage.mgh Thanks, Vale

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Hippocampal/Amygdala subfield segmentation - Anterior Amygdala Area / Medial Nucleus Errors
by David S Lee 04 Jun '19

04 Jun '19

External Email - Use Caution Hello FreeSurfer Experts, I have visually checked 116 subjects that have been processed using Freesurfer's latest hippocampal/amygdala subfield segmentation algorithm (Development version 20180518 <https://surfer.nmr.mgh.harvard.edu/fswiki/HippocampalSubfieldsAndNucleiOfAm…>) and came across 5 cases that failed the QC. My T1s had been processed using FS 5.3, and I used the command "segmentHA_T1.sh" from the latest Dev version. - 3 subjects are missing a mask of the anterior amygdaloid area (AAA), but in the volumetric output, there are values for the regions. - 2 subjects' medical nuclei masks are located in the Putamen region (more superior/detached from the rest of the amygdala). I found the exact same inquiry RE: AAA region posted on April 30, 2019, but I did not see any response. What would be your recommended course of action to resolve these issues? Is there a way to see volumetric measures in the freeview GUI (when clicking a region) to possibly manually trace the missing regions? Thank you for your time, -- David S. Lee Research Specialist Center for Healthy Minds University of Wisconsin - Madison (608) 890-1115

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T2/Flair benefits in freesurfer 6.0
by Aaron Tanenbaum 04 Jun '19

04 Jun '19

External Email - Use Caution I am not too sure if I have asked you this question before. I know the use of a flair or T2 helps with dealing with the dura. I was wondering if there are other benefits?

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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

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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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Freesurfer June 2019