Freesurfer June 2019

freesurfer@nmr.mgh.harvard.edu

82 participants
138 discussions

Applying transformation to surface (e.g. pial) files
by Puzniak, Robert 26 Jun '19

26 Jun '19

External Email - Use Caution Hello, first of all, please forgive me a trivial question, but digging through archives neither provided me with a simple answer, nor gave me an idea how to solve the problem in an elegant way. What I need to do is to apply transformation matrix (actually it's a "ras xform", I can extract it with mri_info and create .xfm file) to the surf/?h.pial files. I'll be very grateful if You could hint me how to approach this, as my attempts with mris_convert, tkregister2 and mri_surf2surf weren't successful. Kind regards, Robert -- M.Sc. Robert Puzniak Marie Curie Fellow - NextGenVis Network Visual Processing Lab, Ophthalmic Dpt. Otto-von-Guericke-Universitaet Leipziger Str. 44 39120 Magdeburg, Germany ++49 (0)391 67 21722

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Interpretation question during LME steps
by Daliah Ross 26 Jun '19

26 Jun '19

External Email - Use Caution Hello FreeSurfer Developers, I am working on running a mass-univariate linear mixed effects model with cortical thickness data, and I have a question about the step that segments the initial covariance estimates into homogenous regions. The next step from the LME webpage (figure; p1 = patch(surf); …) creates figures of the left hemisphere projected onto a sphere and shows clusters of the significant vertices. I am having trouble interpreting this spherical figure. Can it be opened in freesurfer, (i.e. in freeview or tksurfer), so that I can see these clusters projected onto, for example, the inflated cortex (e.g. of fsaverage)? Thank you, Daliah Ross *Daliah Ross* | dross3(a)mail.yu.edu Ph.D. Student, Clinical Psychology with Health Emphasis Ferkauf Graduate School of Psychology Yeshiva University Albert Einstein College of Medicine

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Problem for LGI
by Gwang-Won Kim 26 Jun '19

26 Jun '19

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T2 seq. for hippocampus ??
by Anik Dar 25 Jun '19

25 Jun '19

External Email - Use Caution Hi All, I have 1x1x3 cubic mm T2 and 1x1x1 cubic mm FLAIR, in addition to 1x1x1 cubic mm MPRAGE. Can you please let me know whether I should use only T1 or should I use one of the additional seq. for hippocampal subfield segmentation ? cheers Nik

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Re: [Freesurfer] Reposting a Question RE: Hippocampal/Amygdala subfield segmentation - Anterior Amygdala Area / Medial Nucleus Errors
by David S Lee 25 Jun '19

25 Jun '19

External Email - Use Caution Hello Bruce, Thanks for responding back. To your question RE: "what does the aseg look like in those cases? That is, is it the hippo/amygdala stuff failing or is the root cause further back in the stream (something that caused a bad aseg)" In all 5 cases I mentioned, ASEG looks fine. In other words, ASEG masks for both Amygdala and Hippocampus cover the appropriate voxels relative to subjects' T1 space. However, in all cases (116 subjects I looked at) the latest subfield segmentation seem to *underestimate these regions, meaning ASEG always covers more voxels. Along those lines, large portions of AAA regions are usually marked as "Cerebral Cortex" in ASEG. And the biggest issue again is that though AAA for 3 subjects are not visible in subfield segmentation mask, I get volumetric output. In one case *(Screenshot attached)*, R AAA has single voxel allocated, yet the volume is greater than the Left side which covers more space. Also for the 2 cases in which medial nuclei are marked as Putamen *(Screenshot attached)*, ASEG of putamen and amygdala looks good, but the problematic voxels are darker compared to neighboring voxels *(Screenshot attached)*. This could be tissue damage and/or incorrect identification of "vessel". What would be your recommendation to resolve these issues? Thanks for your time, -- David S. Lee Research Specialist Center for Healthy Minds University of Wisconsin - Madison (608) 890-1115

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Different aparc values
by vittal korann 25 Jun '19

25 Jun '19

External Email - Use Caution Hello FreeSurfer experts, I'm planning to run QDEC on Schizophrenia and controls. To do that I ran recon-all for few subjects in 2 different systems. Both systems have ubuntu 16.04 OS but different freesurfer versions. One is using FS version6 and other is FS version5.3. Just for confirmation, I ran recon-all for the same subjects in 2 above said systems. Now both yield different values for the area. Here I have tabulated the values: fsid Left-Lateral-Ventricle Left-Inf-Lat-Vent Left-Cerebellum-White-Matter Left-Cerebellum-Cortex Left-Thalamus-Proper Left-Caudate Left-Putamen Left-Pallidum 3rd-Ventricle 4th-Ventricle Brain-Stem Left-Hippocampus Left-Amygdala CSF Left-Accumbens-area Left-VentralDC Left-choroid-plexus Right-Lateral-Ventricle Right-Inf-Lat-Vent Right-Cerebellum-White-Matter Right-Cerebellum-Cortex Right-Thalamus-Proper Right-Caudate Right-Putamen Right-Pallidum Right-Hippocampus Right-Amygdala Right-Accumbens-area Right-VentralDC Right-choroid-plexus WM-hypointensities Optic-Chiasm CC_Posterior CC_Mid_Posterior CC_Central CC_Mid_Anterior CC_Anterior INSP015 16157.6 1227.3 11526.1 50572.8 6893 3228.3 5076.3 1927.7 2698.1 2577.8 17706.7 3525.3 1594.6 1164.3 538 4063.9 889.6 10616.9 1179.4 10638.1 50615.7 7252.9 3612.1 5719.7 1788.7 3852.7 1980.1 504.5 3762.4 748.8 728.9 194.4 854.8 393.8 393.9 425.8 1042.1 INSP015 16157.6 1227.3 11526.1 50572.8 6893 3228.3 5076.3 1927.7 2698.1 2577.8 17706.7 3525.3 1594.6 1164.3 538 4063.9 889.6 10616.9 1179.4 10638.1 50615.7 7252.9 3612.1 5719.7 1788.7 3852.7 1980.1 504.5 3762.4 748.8 728.9 194.4 854.8 393.8 393.9 425.8 1042.1 INSP019 7059.6 296 10820.8 42288.3 6177.2 2785.3 4573.8 1793.4 1283.5 1819.9 18958.5 3546.9 1535.8 1212.9 471.2 3741.7 583.6 7378.3 249.5 10200.6 42803.5 6173.9 3078.5 4617.6 1861.3 3638 1599.3 473.7 3532.6 627.1 591.4 270.3 897.7 443.6 497.5 460.7 798.9 INSP019 6962.9 288.8 11995 44004.4 6471.6 2883.8 4653 1888.6 1285.7 1706.1 18983.8 3619.9 1515.5 1117 493.8 3790.8 620.7 7446.8 273.6 10674.7 42678.1 6220.8 3109.2 4498.1 1943 3540.7 1658.3 499.8 3656.3 652 735.6 189.4 863.6 470.6 434.4 502.6 749.1 IYBA009 10661.7 644 16029.1 61364.8 7534.2 4416.4 5562.8 2279.9 1335.2 1775.6 24381.2 3787.8 1666.3 970.4 624.4 4286.9 709.1 9079.2 803.7 15172.2 59565.1 6989.7 4334.1 5550.7 2267.8 3928.2 1743.1 582.4 4465.2 676.6 728 195.6 667.6 426.8 363.9 362.4 929.1 IYBA009 10730.6 722.5 16662.8 60503.6 7686.1 4328.3 5430.1 2256.9 1365 1720.2 24139.9 3749.1 1635.9 995.6 639.8 4374 573.9 8963.9 795.2 15817.6 60176.1 7044.7 4251.9 5423.8 2241.1 3715.8 1749.2 600.2 4418.1 623.8 953.8 155 664.6 444.3 401.5 370.4 924.9 The above variation is because of different versions or each time freesurfer yields different values? Could you please educate me more on this. Because if the freesurfer version is the issue then I need to run all analysis in one system which will take a lot of time. Thanks & regards Vittal

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Re: [Freesurfer] DesikanKilliany ROI for mri_glmfit
by Greve, Douglas N.,Ph.D. 24 Jun '19

24 Jun '19

Try running it wiith --help to get docs and examples On 6/24/19 4:52 PM, Tammi Kral wrote: > > External Email - Use Caution > > This may be a naïve question - but this function > (mri_annotation2label) appears to be for use with individual subject > data - how do I use it with the DK atlas? When I provide the DK atlas > file as the "subject" input I get an error because it is looking for a > standard subject directory structure with the normal files (e.g. in > 'surf'). > > > Or am I creating a label for each individual subject to reference with > mri_glmfit? > > ------------------------------------------------------------------------ > *From:* Tammi Kral > *Sent:* Friday, June 21, 2019 9:18:46 PM > *To:* Greve, Douglas N.,Ph.D. > *Subject:* Re: [Freesurfer] DesikanKilliany ROI for mri_glmfit > > Thank you, I will try what you have suggested. Yes, it is a > surface-based analysis. > > ------------------------------------------------------------------------ > *From:* Greve, Douglas N.,Ph.D. <DGREVE(a)mgh.harvard.edu> > *Sent:* Friday, June 21, 2019 7:12:26 PM > *To:* Tammi Kral > *Subject:* Re: [Freesurfer] DesikanKilliany ROI for mri_glmfit > Can you give more information? Eg, is this a surface-based or > volume-based study? If you are doing a surface-based and want to > confine the results to the insula, then you can use > mri_annotation2label to break the DK atlas into individual labels, > then pass the insula label to mri_glmfit through the --label option. > > On 6/19/2019 4:32 AM, Tammi Kral wrote: >> >> External Email - Use Caution >> >> Hello, >> >> >> I would like to use the insula label/ROI from the DesikanKilliany >> atlas with mri_glmfit. How do I reference this label, as I don't see >> a LUT for this atlas. >> >> >> I appreciate any suggestions. >> >> >> Thanks, >> >> >> Tammi R.A. Kral, M.S. >> -- >> Doctoral Candidate, Psychology >> University of Wisconsin-Madison >> Center for Healthy Minds >> Waisman Brain Imaging Laboratory >> >> >> _______________________________________________ >> Freesurfer mailing list >> Freesurfer(a)nmr.mgh.harvard.edu <mailto:Freesurfer@nmr.mgh.harvard.edu> >> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >

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base frame respectively reference frame for computation of FS-FAST motion parameters
by Pfannmoeller, Joerg Peter 24 Jun '19

24 Jun '19

Hello, as far as I can see FS-FAST uses the 0th frame as the reference frame in the computation of the motion parameters using the function . However, in the visualization of the translations the motion parameters seem to use the middle frame as the reference point. Is this the case? What is the motivation for setting the base frame to the first frame? Best Joerg

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I have a question for "matlabruntime"
by Gwang-Won Kim 24 Jun '19

24 Jun '19

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Unanswered question regarding including covariates in the fsgd file and the contrast matrix
by Basavaraju, Rakshathi 24 Jun '19

24 Jun '19

External Email - Use Caution Hi all FS users, I have the basic doubt of including age and gender as co-variates for a cortical thickness comparison between 2 groups. I read extensively many mails answering these questions but still could not get a satisfactory answer for the question. As I have 2 discrete variables i.e. Group with 2 levels and gender with 2 levels and one continuous variable of age my contrast matrix should be like this: [0 0 0 0 0 0 0 0] which is [malegroup1 femalegroup1 malegroup2 femalegroup2 age.malegroup1 age.femalegroup1 age.malegroup2 age.femalegroup2] I understood that if I have to test the effect of only the groups my contrast matrix should be: [0.5 0.5 -0.5 -0.5 0 0 0 0] What should be my contrast matrix if I have to include age and gender as covariates respectively? I know gender cannot be included as columns of 1s and 0s by my reading of previous mails. In one of the mail I read that if we want to test for interaction of group and gender (disregarding effect of age) the contrast matrix file should be: [0.5 -0.5 -0.5 0.5 0 0 0 0] But is testing for gender as a covariate same as testing group*gender interaction? I do not feel so. Hence requesting you all to throw some clarity on this. If this is not the way to study gender as a covariate how else should the contrast matrix be written? And regarding age should it be four 0.5s for the last 4 columns of the matrix if we want to study age as a covariate? Kindly let know. Finally I want a contrast matrix that studies the group differences in cortical thickness covarying for the effect of age and gender. Kindly help me. Thanks, Dr. Rakshathi Basavaraju (MD Psychiatry) Postdoctoral Research Scientist Taub Institute Columbia University Irving Medical Centre 622 West, 168th Street, New York - 10032 E-Mail: rb3419(a)cumc.columbia.edu<mailto:rb3419@cumc.columbia.edu> http://www.wellcomedbt.org/fellowsprofile/dr-rakshathi-basavaraju-288

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Freesurfer June 2019