Freesurfer

freesurfer@nmr.mgh.harvard.edu

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30068 discussions

Re: [Freesurfer] PVC on DCE MRI
by Shen, Qian 07 Nov '24

07 Nov '24

External Email - Use Caution Hi FreeSurfer Team, We are looking to apply voxelwise PVC on our dynamic contrast-enhanced (DCE) MRI data using methods implemented in PETSurfer. Our DCE MRI data voxelsize =1x1x5mm, and we have used the Patlak model to estimate the transfer coefficient (Ktrans). We are interested in both GM and WM signals. I have a few specific questions regarding the applicability and execution of PVC in our case: 1. Given that the M?ller-G?rtner (MG) method assumes constant WM signals and zero CSF signals (which is more suited to PET studies), it seems this may not be optimal for us. Would the RBV or Meltzer (MZ) methods be more appropriate for our DCE MRI data? 2. Should PVC be applied to the 4D dynamic DCE data before dynamic modeling, or directly to the 3D Ktrans map after modeling? 3. Does the point spread function (PSF) of the MRI scanner cause more PVE than the TFE? Additionally, I have one more question about the outputs of the MG PVC method. Could you clarify the role of mgx.gm in the results? Does it the combination of mgx.ctxgm and mgx.subctxgm? Any help is appreciated. Many thanks! Shen

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mri_glmfit-sim Error for Custom Threshold
by Sujeevini Sujanthan 07 Nov '24

07 Nov '24

External Email - Use Caution Dear Freesurfer Experts, I'm encountering an error when attempting to run mri_glmfit-sim with a custom threshold of 1.6. I've already generated the necessary tables using mri_mcsim for this threshold. ############## mri_glmfit-sim --glmdir glm_wls --mczsim-label {ROI} --mczsim 1.6 abs --cwp 0.05 ERROR: thresh = 1.6, must be 1.3, 2.0, 2.3, 3.0, 3.3, 4.0 ############## Could you please advise on what I can do to fix this? Thank you for your time, Sujeevini

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glmfit-sim question
by 이종훈(보건과학대학 의공학부) 07 Nov '24

07 Nov '24

External Email - Use Caution Dear Freesurfer expert, I hope this email finds you well. I am currently working on a project involving FreeSurfer's cluster-wise correction methods, and I encountered an unexpected result when adjusting the Cluster-Forming Threshold (CFT) and Cluster-Wise Probability (CWP) values. I would greatly appreciate your expertise on this matter. In my analysis, I observed that some regions were not detected when using a CFT of 1.3 and a CWP of 0.05. However, these regions emerged as significant when I increased the CFT to 2.0 while keeping the CWP constant at 0.05. This finding appears counterintuitive, as a higher CFT typically results in fewer clusters being detected due to the increased threshold for significance. Could you please help clarify why this phenomenon might occur? Specifically: 1. How might the higher CFT (2.0) interact with the CWP (0.05) to reveal regions that did not appear with a lower CFT (1.3)? 2. Is it possible that the increase in CFT reduces noise or increases signal clarity in such a way that previously undetected clusters reach significance? Thank you very much for your time and guidance. I look forward to any insights you can provide on this topic. Jonghun Lee Master's Student, Advanced Image Processing Technology Lab Yonsei University

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Edit control points
by Mariana Falcao 04 Nov '24

04 Nov '24

External Email - Use Caution Good morning, I am trying to reconstruct the tracts that were poorly reconstructed by tracula by editing control points of each tract (I already tried setting reinit=1 but it didn't work). This process is described in this article <https://secure-web.cisco.com/10TqvkUm9LODp9Pl7m0fdHfu6lBQw4pYr1HxabnRgrdPw6…>. In step 6 of section 'Data Processing and Quality Control' of that mentioned article, the authors say: "we converted the coordinates of the control points (https://secure-web.cisco.com/1OuJo9rzEYM7J_5SylW2YYQuH6HrdRZMFJLFYsT1uI6-2l…) from voxel space to Right-Anterior-Superior (RAS, anatomical coordinates) in order to view and edit in FreeSurfer’s freeview toolbox." I am confused about which transformation I have to do (from the ones mentioned in the link of step 6). Currently, without any transformation made, I see the control points (dlabel/syn/acomm_avg16_syn_bbr_cpts_7.txt) for the anterior commissure as in the figure attached in this email. As you can see, the points don't seem to be in diffusion space (but rather in the template space, MNI305). I am assuming that the transformation mentioned in the article sets the points in the position where the anterior commissure is supposed to be (and then the idea would be to edit them, save them and run trac-all -path -c for this tract). So my question here is: which transformation is it? I am inclined to believe it is the 4th mentioned in the link <https://secure-web.cisco.com/1OuJo9rzEYM7J_5SylW2YYQuH6HrdRZMFJLFYsT1uI6-2l…>. If you believe I am on the wrong track and there's abettert alternative, please let me know. Warm regards, Mariana [image: imagen.png]

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Re: [Freesurfer] recon-all-clinical output brainvol.stats vs synthseg.vol.csv
by Melissa Marie Rundle 30 Oct '24

30 Oct '24

External Email - Use Caution Hello, Recon-all-clinical outputs several files, including brainvol.stats and synthseg.vol.csv, that have volumetric data that don’t match each other. See example data below. Are the stats for brainvol (as well as lh.aprac.stats/rh.aprac.stats) generated from the synthseg processing? And if not, how is the data generated? Thanks so much for your help, Melissa Rundle In brainvol.stats: Left hemisphere cerebral white matter volume=225511.42 mm3 Left hemisphere cortical gray matter volume=194309.18 mm3 In synthseg.vol.csv: left cerebral white matter volume=224286.48 mm3 left cerebral cortex volume=252060.19 mm3 ________________________________ This electronic message is intended only for the use of the individual(s) and entity named as recipients in the message. If you are not an intended recipient of this message, please notify the sender immediately and delete the material from any computer. Do not deliver, distribute or copy this message, and do not disclose its contents or take any action in reliance on the information it contains. Thank you.

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Error During T2/FLAIR Pial Surface Refinement
by Thomas Kaufmann 29 Oct '24

29 Oct '24

External Email - Use Caution Hello FreeSurfer Developers, I'm attempting to refine pial surfaces with T2/FLAIR images as described here ( https://secure-web.cisco.com/1AH1BRBqXr5DfxhMfqvYMi7G1gSsW58-k5PUb3k7qBej25…) For some of my subjects I get the following error during the mris_place_surface subprocess when I run recon-all: error: MRIhistogramLabelRegion: constant image error: MRIhistogramLabelRegion: constant image Segmentation fault The error occurs independent of whether I process T1 and T2 images together with -all or if I run only -autorecon3 with the T2 or FLAIR images added. I've searched the list and while similar errors have been reported, no solutions have been proposed. Does anyone have any thoughts on how to troubleshoot this one? 1) FreeSurfer version: freesurfer-macOS-darwin_x86_64-7.4.1-20230614-7eb8460 2) Platform: macOS Sonoma 14.6.1 3) uname -a: Darwin MacBook-Air-M3 23.6.0 Darwin Kernel Version 23.6.0: Mon Jul 29 21:14:04 PDT 2024; root:xnu-10063.141.2~1/RELEASE_ARM64_T8122 arm64 4) recon-all.log: relevant section below Thank you! Thomas mris_place_surface --adgws-in ../surf/autodet.gw.stats.lh.dat --seg aseg.presurf.mgz --wm wm.mgz --threads 8 --invol brain.finalsurfs.mgz --lh --i ../surf/lh.pial.T1 --o ../surf/lh.pial.T2 --pial --nsmooth 0 --rip-label ../label/lh.cortex+hipamyg.label --pin-medial-wall ../label/lh.cortex.label --white-surf ../surf/lh.white --aparc ../label/lh.aparc.annot --repulse-surf ../surf/lh.white --mmvol T2.mgz T2 Reading in input surface ../surf/lh.pial.T1 Not smoothing input surface Area 280714 0.42434 0.32508 0.000178 6.1090 Corner 842142 60.00000 30.99319 0.049953 179.7466 Edge 421071 1.04711 0.48130 0.006015 7.4374 Hinge 421071 18.87838 25.11022 0.000011 179.9979 Reading white surface coordinates from ../surf/lh.white Reading repulsion surface coordinates from ../surf/lh.white Reading in aparc ../label/lh.aparc.annot [DEBUG] CTABreadFromBinaryV2(): ct->nentries=36, num_entries_to_read=36 Reading in input volume brain.finalsurfs.mgz Reading in seg volume aseg.presurf.mgz Reading in wm volume wm.mgz MRIclipBrightWM(): nthresh=15378, wmmin=5, clip=110 MRIfindBrightNonWM(): 1814 bright non-wm voxels segmented. Masking bright non-wm for pial surface mid_gray = 67.5589 MRImask(): AllowDiffGeom = 1 MRImask(): AllowDiffGeom = 1 MRImask(): AllowDiffGeom = 1 Ripping frozen voxels Ripping vertices not in label ../label/lh.cortex+hipamyg.label MRISripNotLabel() ripped 6543/140359 vertices (133816 unripped) INFO: rip surface needed but not specified, so using input surface Ripping segs (eg, WMSA, BG, frozen) Starting MRISripSegs() d = (-2 2 0.5) segnos: 247 MRISripSegs(): -2 2 0.5 ripped 0 Reading in multimodal volume T2.mgz using multi modal weights vertex 70180: xyz = (-39.3637,-26.8713,28.9107) oxyz = (-42.1603,-27.2597,31.4024) wxzy = (-42.1603,-27.2597,31.4024) pxyz = (-39.3637,-26.8713,28.9107) CBVO Creating mask 140359 n_averages 4 Iteration 0 ========================================= n_averages=4, current_sigma=2 Computing pial target locations using multimodal (1) starting MRIScomputePialTargetLocationsMultiModal() max_outward_dist = 3, sample_dist = 0.1, pix_size = 1, whalf = 7 T2_min_inside = 110, T2_max_inside 300, T2_min_outside = 130, T2_max_outside 300 inside_peak_pct = 0.1, 0.01, outside_peak_pct = 0.5, 0.5 wm_weight = 3, nlabels=0, contrast_type=1 Changed 198177 aseg cortex voxels to 0 Creating lowres distance volumes t=0.0164299 Creating white distance volumes t=0.307498 (box.dx, box.dy, box.dz) = (132, 242, 326) (region->dx, region->dy, region->dz) = (132, 242, 326) (region->dx, region->dy, region->dz) = (132, 242, 326) Creating pial distance volumes t=0.609579 (box.dx, box.dy, box.dz) = (144, 256, 336) (region->dx, region->dy, region->dz) = (144, 256, 336) (region->dx, region->dy, region->dz) = (144, 256, 336) locating cortical regions not in interior range [110.0 --> 300.0], and not in exterior range [130.0 --> 300.0] t = 0.984043 Starting loop over 140359 vertices vno = 0, t = 0.984043 error: MRIhistogramLabelRegion: constant image error: MRIhistogramLabelRegion: constant image Segmentation fault

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Edit control points for better tract reconstruction
by Mariana Falcao 29 Oct '24

29 Oct '24

External Email - Use Caution Dear TRACULA experts, As you can see in the figure attached to this email, there are 3 tracts that were not able to be properly reconstructed (right fornix and left and right corticospinal tract). What I have tried: 1) Setting reinit=1 in the configuration file and re-run TRACULA; 2) Changing the number of control points for each tract, according to the pathlist.txt (even though the second column refers to the default control points, I am not sure what the first column means); My idea now would be to edit the control points manually but I don't know which file contains those points. I am assuming that each tract must have a file with the respective control points. This process is described in this article <https://secure-web.cisco.com/1Syob_RQa8CnqTu5J98-5wBZC9rpcTVD0Wgicm76PjaNZv…>. I am looking for something such as Figure 2 and 3 in that article. I have looked into the email archive and didn't find anything related to this problem. Best wishes, Mariana

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Re: [Freesurfer] infantFS: expected outputs
by Zoellner, Frank 24 Oct '24

24 Oct '24

External Email - Use Caution Hi Lilla, and is there a reason why ? I mean are these regions (labels) not detectable in the infants or did you just not include them ? Since the adult freesurfer pipeline could segment them I am wondering why they are not labeled in the infant atlas… Yours Frank ---------------- adj. Prof. Dr. Frank Zoellner Acting head Computer Assisted Clinical Medicine Mannheim Institute for Intelligent Systems in Medicine Medical Faculty Mannheim Heidelberg University Theodor-Kutzer-Ufer 1-3 D-68167 Mannheim Phone: +49 (0)621 3835117 Fax: +49 (0)621 3835123 Email: Frank.Zoellner(a)MedMa.Uni-Heidelberg.de<mailto:Frank.Zoellner@MedMa.Uni-Heidelberg.de> Web: https://secure-web.cisco.com/1RqQnv7kxvO9_w5Srsw77gD-ZtwN2XNsKEWYAXYh8x70-3… Von: <freesurfer-bounces(a)nmr.mgh.harvard.edu> im Auftrag von "Zollei, Lilla,Ph.D." <LZOLLEI(a)MGH.HARVARD.EDU> Antworten an: "freesurfer(a)nmr.mgh.harvard.edu" <freesurfer(a)nmr.mgh.harvard.edu> Datum: Donnerstag, 24. Oktober 2024 um 03:59 An: "freesurfer(a)nmr.mgh.harvard.edu" <freesurfer(a)nmr.mgh.harvard.edu> Betreff: Re: [Freesurfer] infantFS: expected outputs Dear Frank, You are correct. The list of segmentation labels is not 100% the same. For the infantFS segmentation labels you can refer to Table 1 in https://secure-web.cisco.com/1vWMGdCD3mZXs2SmPbxmXci6igleKzDLTd49jV-LXb9Ovp… Best, Lilla ________________________________ From: freesurfer-bounces(a)nmr.mgh.harvard.edu <freesurfer-bounces(a)nmr.mgh.harvard.edu> on behalf of Zoellner, Frank <Frank.Zoellner(a)medma.uni-heidelberg.de> Sent: Monday, September 23, 2024 4:31 AM To: Freesurfer support list <freesurfer(a)nmr.mgh.harvard.edu> Subject: Re: [Freesurfer] infantFS: expected outputs External Email - Use Caution Dear Lilla, Besides the differences in the files, when looking at the segmentations we wondered why there are some labels zero in the aseg stats file. These are : Left-Inf-Lat-Vent CSF Right-Inf-Lat-Vent Brain-Stem Left-vessel Left-choroid-plexus Right-vessel Right-choroid-plexus 5th ventrikel WM-hypointensities We also did a cross check and had run the same subject with the normal freesurfer pipeline and here there have been segmentations for the above structures. Maybe you have an idea what is happening here ? or are these not included in the atlas? Thanks in advance Yours Frank ----------- adjunct Prof. Dr. Frank Zoellner Acting head Computer Assisted Clinical Medicine Mannheim Institute for Intelligent System in Medicine Medical Faculty Mannheim Heidelberg University Theodor-Kutzer-Ufer 1-3 D-68167 Mannheim Phone: +49 (0)621 3835121 Fax: +49 (0)621 3835123 Email: Frank.Zoellner(a)MedMa.Uni-Heidelberg.de<mailto:Frank.Zoellner@MedMa.Uni-Heidelberg.de> Web: https://secure-web.cisco.com/1RqQnv7kxvO9_w5Srsw77gD-ZtwN2XNsKEWYAXYh8x70-3… Von: freesurfer-bounces(a)nmr.mgh.harvard.edu <freesurfer-bounces(a)nmr.mgh.harvard.edu> Im Auftrag von Zollei, Lilla,Ph.D. Gesendet: Sonntag, 22. September 2024 16:12 An: freesurfer(a)nmr.mgh.harvard.edu Betreff: Re: [Freesurfer] infantFS: expected outputs Hi Marlene, This is correct. Even though infant_recon_all is trying to mimic the output folder structure and follows the FreeSrufer naming convention, it does not generate all of the files that the adult version does. Lilla ________________________________ From: freesurfer-bounces(a)nmr.mgh.harvard.edu<mailto:freesurfer-bounces@nmr.mgh.harvard.edu> <freesurfer-bounces(a)nmr.mgh.harvard.edu<mailto:freesurfer-bounces@nmr.mgh.harvard.edu>> on behalf of Marlene Staginnus <ms2290(a)bath.ac.uk<mailto:ms2290@bath.ac.uk>> Sent: Monday, September 16, 2024 9:57 AM 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>> Subject: [Freesurfer] infantFS: expected outputs External Email - Use Caution Dear FreeSurfer Team, Apologies in case I missed this elsewhere, but I was wondering whether there is any information on what the expected outputs of running infant_ recon_all are, similar to this (https://secure-web.cisco.com/1mA29bmjZg8MZLmt_5OWSzYbAcnPRT4qfP6KTFLCwUY69A…) for the adult pipeline? I am asking as after testing the pipeline using the example participant provided on openneuro (https://secure-web.cisco.com/1eG9UEoGKfhMXUoWW953Ozv01X5SscPRanNwg37dq-iV0q…, I’ve noticed that some of the output differs from the adult version and I wanted to ensure that everything is running correctly before applying it to our data. For example, there is no ‘orig’ subdirectory or orig.mgz file in the ~/mri folder. Similarly, fewer files are included in the ~/stats folder (only: brainvol.stats, lh.aparc.stats, rh.aparc.stats) although I was able to able to generate other files (e.g., aseg.stats) using mri_segstats. Overall, only the following folders are generated following recon-all without errors: label, log, mri, stats, and surf. Is this correct or might there be something going wrong on my end? 1) FreeSurfer version: infant-dev-4a14499-20210109-4a14499 2) Platform: CentOS release 7 3) uname -a: Linux fhpc-1840 6.8.0-40-generic #40~22.04.3-Ubuntu SMP PREEMPT_DYNAMIC Tue Jul 30 17:30:19 UTC 2 x86_64 x86_64 x86_64 GNU/Linux 4) infant_recon_all log: see attached Thank you in advance! Best wishes, Marlene

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infantFS: expected outputs
by Marlene Staginnus 23 Oct '24

23 Oct '24

External Email - Use Caution Dear FreeSurfer Team, Apologies in case I missed this elsewhere, but I was wondering whether there is any information on what the expected outputs of running infant_ recon_all are, similar to this (https://surfer.nmr.mgh.harvard.edu/fswiki/ReconAllOutputFiles) for the adult pipeline? I am asking as after testing the pipeline using the example participant provided on openneuro (https://openneuro.org/datasets/ds004776/versions/1.0.0, I’ve noticed that some of the output differs from the adult version and I wanted to ensure that everything is running correctly before applying it to our data. For example, there is no ‘orig’ subdirectory or orig.mgz file in the ~/mri folder. Similarly, fewer files are included in the ~/stats folder (only: brainvol.stats, lh.aparc.stats, rh.aparc.stats) although I was able to able to generate other files (e.g., aseg.stats) using mri_segstats. Overall, only the following folders are generated following recon-all without errors: label, log, mri, stats, and surf. Is this correct or might there be something going wrong on my end? 1) FreeSurfer version: infant-dev-4a14499-20210109-4a14499 2) Platform: CentOS release 7 3) uname -a: Linux fhpc-1840 6.8.0-40-generic #40~22.04.3-Ubuntu SMP PREEMPT_DYNAMIC Tue Jul 30 17:30:19 UTC 2 x86_64 x86_64 x86_64 GNU/Linux 4) infant_recon_all log: see attached Thank you in advance! Best wishes, Marlene

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Extracting generic gradient vector
by Ashwati Vipin (Dr) 23 Oct '24

23 Oct '24

External Email - Use Caution Dear Freesurfer developers, I am trying to replicate a multi shell DTI protocol from one scanner to another. However I need the generic gradient vectors so that the protocol can be replicated. Is there a script in freesurfer that can reverse engineer the relative direction coordinates and normalisation of vector strengths so that this file can be used in the scanner console to define all the parameters of this sequence and replicate it across different scanners? Please help!! Thank you so much!! Best, Ashwati -- Ashwati Vipin (PhD) Research Fellow, Dementia Research Centre (Singapore) Clinical Sciences Building 11 Mandalay Road, Singapore 308232 T: +65 6592 3963 E: ashwati.vipin(a)ntu.edu.sg<mailto:ashwati.vipin@ntu.edu.sg> W: https://secure-web.cisco.com/1UxqE_XW7QCy7OrGxdUFafNIAzhq2UJBPlV7TRZ1Pg2bya… [A close-up of a logo Description automatically generated] ________________________________ CONFIDENTIALITY: This email is intended solely for the person(s) named and may be confidential and/or privileged. If you are not the intended recipient, please delete it, notify us and do not copy, use, or disclose its contents. Towards a sustainable earth: Print only when necessary. Thank you.

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