Freesurfer

freesurfer@nmr.mgh.harvard.edu

19 participants
30088 discussions

Command not found
by Samer Muhareb 24 Sep '19

24 Sep '19

External Email - Use Caution Hello, I am having trouble adding Freesurfer onto my PC. I have the program downloaded, but when I attempt to input a command from the Freesurfer program, it tells me that my command was not found. [image: image.png] This is my first time downloading a program to use in the command line without it being done for me, so I am not super clear on how to go about solving this issue or may have missed a crucial step. I was suggested to add the program onto the path but I am not really sure how to do that. Any ideas or suggestions will be very helpful! I am using git bash on my windows, if that is helpful Thanks for taking the time to look into this, it is greatly appreciated. Best, Samer Muhareb

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Error during processing data. mris_make_surfaces malloc: *** error for object 0x2431900024317: pointer being freed was not allocated.
by Троицкий Антон Александ рович 24 Sep '19

24 Sep '19

External Email - Use Caution Hello FreeSurfer Developers, during the processing of patient data an error occurred. I don’t clearly understand a reason for this error. Technical description of this error is mris_make_surfaces(10174,0x7fffbf9553c0) malloc: *** error for object 0x2431900024317: pointer being freed was not allocated *** set a breakpoint in malloc_error_break to debug 000: dt: 0.0000, sse=991989.1, rms=2.913 021: dt: 0.5000, sse=841468.7, rms=1.605 (44.916%) 022: dt: 0.5000, sse=803776.9, rms=1.267 (21.055%) rms = 1.24, time step reduction 1 of 3 to 0.250... 023: dt: 0.5000, sse=793308.4, rms=1.242 (1.982%) Abort My suggestion is that the error associated with memory allocation and its reading. Is there any suggestion about why it happened and how can I prevent it in the future? Also, I've attached the recon-all.log in case it's of any use. 1) FreeSurfer version: freesurfer-Darwin-OSX-stable-pub-v6.0.0 2) Platform: macOS Sierra 10.12.6 3) uname -a: Darwin mac-2ap023-2.fccho-moscow.ru 16.7.0 Darwin Kernel Version 16.7.0: Thu Jan 11 22:59:40 PST 2018; root:xnu-3789.73.8~1/RELEASE_X86_64 x86_64 4) recon-all.log: see attached

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help! Hippocampal subfield segmentation with FS development version
by Liwen Zhang 24 Sep '19

24 Sep '19

External Email - Use Caution Hello freesurfer experts, I previously applied hippocampal subfield segmentation using FS v.6.0. I am now trying to devide subfields into head/body where applicable using FS development version (latest version). However, I encountered the following problems/quesetions: 1) X represents certain subfield (volume)X_head + X_body (from FS dev) ~= X (from FS v.6.0) What possibly causes this volume discrepancy between FS dev and FS v.6.0? Is the head/body segmentation template in FS dev based on the same ex-vivo template as used in FS v.6.0? 2) Related to 1), subfield volume as obtained from FS v.6.0 generally larger than that from FS dev (not for all subfields though) I processed T1 images with FS v.6.0 and then applied hippocampal segmentation with both FS v.6.0 and FS dev. Any suggestions/comments would be greatly appreicated! Thank you for your time and help in advance! Best, Liwen

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DPABISurf V1.2 Is Released
by YAN Chao-Gan 23 Sep '19

23 Sep '19

External Email - Use Caution Dear Colleagues, We are pleased to announce the release of DPABISurf V1.2! DPABISurf is a surface-based resting-state fMRI data analysis toolbox evolved from DPABI/DPARSF, as easy-to-use as DPABI/DPARSF. DPABISurf is based on fMRIPprep 1.5.0 (Esteban et al., 2018)(RRID:SCR_016216), and based on FreeSurfer 6.0.1 (Dale et al., 1999)(RRID:SCR_001847), ANTs 2.2.0 (Avants et al., 2008)(RRID:SCR_004757), FSL 5.0.9 (Jenkinson et al., 2002)(RRID:SCR_002823), AFNI 20160207 (Cox, 1996)(RRID:SCR_005927), SPM12 (Ashburner, 2012)(RRID:SCR_007037), PALM alpha112 (Winkler et al., 2016), GNU Parallel (Tange, 2011), MATLAB (The MathWorks Inc., Natick, MA, US) (RRID:SCR_001622), Docker (https://docker.com) (RRID:SCR_016445), and DPABI V4.2 (Yan et al., 2016)(RRID:SCR_010501). DPABISurf provides user-friendly graphical user interface (GUI) for pipeline surface-based preprocessing, statistical analyses and results viewing, while requires no programming/scripting skills from the users. <http://www.rfmri.org/dpabi> The DPABISurf pipeline first converts the user specified data into BIDS format (Gorgolewski et al., 2016), and then calls fMRIPprep 1.5.0 docker to preprocess the structural and functional MRI data, which integrates FreeSurfer, ANTs, FSL and AFNI. With fMRIPprep, the data is processed into FreeSurfer fsaverage5 surface space and MNI volume space. DPABISurf further performs nuisance covariates regression (including ICA-AROMA) on the surface-based data (volume-based data is processed as well), and then calculate the commonly used R-fMRI metrics: amplitude of low frequency fluctuation (ALFF) (Zang et al., 2007), fractional ALFF (Zou et al., 2008), regional homogeneity (Zang et al., 2004), degree centrality (Zuo and Xing, 2014), and seed-based functional connectivity. DPABISurf also performs surface-based smoothing by calling FreeSurfer’s mri_surf2surf command. These processed metrics then enters surfaced-based statistical analyses within DPABISurf, which could perform surfaced-based permutation test with TFCE by integrating PALM. Finally, the corrected results could be viewed by the convenient surface viewer DPABISurf_VIEW, which is derived from spm_mesh_render.m. <http://www.rfmri.org/dpabi> DPABISurf is designed to make surface-based data analysis require minimum manual operations and almost no programming/scripting experience. We anticipate this open-source toolbox will assist novices and expert users alike and continue to support advancing R-fMRI methodology and its application to clinical translational studies. DPABISurf is open-source and distributed under GNU/GPL, available with DPABI at http://www.rfmri.org/dpabi. It supports Windows 10 Pro, MacOS and Linux operating systems. You can run it with or without MATLAB. 1. With MATLAB. 1.1. Please go to http://www.rfmri.org/dpabi to download DPABI. 1.2. Add with subfolders for DPABI in MATLAB's path setting. 1.3. Input 'dpabi' and then follow the instructions of the "Install" Button on DPABISurf. 2. Without MATLAB. 2.1. Install Docker. 2.2. Terminal: docker pull cgyan/dpabi 2.3. Terminal: docker run -d --rm -v /My/FreeSurferLicense/Path/license.txt:/opt/freesurfer/license.txt -v /My/Data/Path:/data -p 5925:5925 cgyan/dpabi x11vnc -forever -shared -usepw -create -rfbport 5925 /My/FreeSurferLicense/Path/license.txt: Where you stored the FreeSurferLicense got from https://surfer.nmr.mgh.harvard.edu/registration.html. /My/Data/Path: This is where you stored your data. In Docker, the path is /data. 2.4. Open VNC Viewer, connect to localhost:5925, the password is 'dpabi'. 2.5. In the terminal within the VNC Viewer, input "bash", and then input: /opt/DPABI/DPABI_StandAlone/run_DPABI_StandAlone.sh ${MCRPath} Now please enjoy the StandAlone version of DPABISurf with GUI! If you don't want to run with GUI, you can also call the compiled version of DPABISurf_run. E.g., docker run -it --rm -v /My/FreeSurferLicense/Path/license.txt:/opt/freesurfer/license.txt -v /My/Data/Path:/data cgyan/dpabi /bin/bash /opt/DPABI/DPABI_StandAlone/run_DPABISurf_run_StandAlone.sh ${MCRPath} /data/DPABISurf_Cfg.mat New features of DPABISurf_V1.2_190919 within DPABI_V4.2_190919 (download at http://rfmri.org/dpabi, please also update the docker file by: docker pull cgyan/dpabi): 1. DPABISurf_V1.2_190919 updated. 1.1. A quality control module was added to DPABISurf. Now users can quality control surface reconstruction, EPI to T1 registration and T1 to MNI registration for all the subjects in one HTML file, respectively (based on fmriprep 1.5.0). For volume-based analysis, users can also generate group mask for DPABISurf, and exclude subjects by thresholding coverage and head motion. 1.2. DPABISurf now also output sulcus depth and volume in fsaverage and fsaverage5 spaces for statistical analysis. 1.3. In results organizer of DPABISurf, the redundant files would not be organized now. In addition, the fmriprep and freesurfer files were backed up, while excluding T1 image that may have privacy information such as face. 2. DPABI_VIEW has a new function "Surface View with DPABISurf_VIEW" now. This function will convert the files to fsaverage surface using freesurfer's mri_vol2surf command. Then the results were displayed by calling DPABISurf_VIEW to generate surface-based picture. Tips: 1) For Linux or Mac OS, please start matlab from terminal in order to reach docker in DPABI (e.g., Linux: matlab; Mac: open /Applications/MATLAB_R2018a.app/). 2) Before running DPABISurf_Pipeline, you can test the docker environment by running DPABI->DPABISurf->Utilities->Volume-Surface Projector. If the file can be successfully projected to surface, then the software is all set. References: - Ashburner, J. (2012). SPM: a history. *Neuroimage*, 62(2), 791-800, doi:10.1016/j.neuroimage.2011.10.025. - Avants, B.B., Epstein, C.L., Grossman, M., Gee, J.C. (2008). Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. *Med Image Anal*, 12(1), 26-41, doi:10.1016/j.media.2007.06.004. - Cox, R.W. (1996). AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. *Comput Biomed Res*, 29(3), 162-173. - Dale, A.M., Fischl, B., Sereno, M.I. (1999). Cortical surface-based analysis. I. Segmentation and surface reconstruction. *Neuroimage*, 9(2), 179-194, doi:10.1006/nimg.1998.0395. - Esteban, O., Markiewicz, C.J., Blair, R.W., Moodie, C.A., Isik, A.I., Erramuzpe, A., Kent, J.D., Goncalves, M., DuPre, E., Snyder, M., Oya, H., Ghosh, S.S., Wright, J., Durnez, J., Poldrack, R.A., Gorgolewski, K.J. (2018). fMRIPrep: a robust preprocessing pipeline for functional MRI. *Nat Methods*, doi:10.1038/s41592-018-0235-4. - Gorgolewski, K.J., Auer, T., Calhoun, V.D., Craddock, R.C., Das, S., Duff, E.P., Flandin, G., Ghosh, S.S., Glatard, T., Halchenko, Y.O., Handwerker, D.A., Hanke, M., Keator, D., Li, X., Michael, Z., Maumet, C., Nichols, B.N., Nichols, T.E., Pellman, J., Poline, J.B., Rokem, A., Schaefer, G., Sochat, V., Triplett, W., Turner, J.A., Varoquaux, G., Poldrack, R.A. (2016). The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments. *Sci Data*, 3, 160044, doi:10.1038/sdata.2016.44. - Jenkinson, M., Bannister, P., Brady, M., Smith, S. (2002). Improved optimization for the robust and accurate linear registration and motion correction of brain images. *Neuroimage*, 17(2), 825-841. - Tange, O. (2011). Gnu parallel-the command-line power tool. *The USENIX Magazine*, 36(1), 42-47. - Winkler, A.M., Ridgway, G.R., Douaud, G., Nichols, T.E., Smith, S.M. (2016). Faster permutation inference in brain imaging. *Neuroimage*, 141, 502-516, doi:10.1016/j.neuroimage.2016.05.068. - Yan, C.G., Wang, X.D., Zuo, X.N., Zang, Y.F. (2016). DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging. *Neuroinformatics*, 14(3), 339-351, doi:10.1007/s12021-016-9299-4. - Zang, Y., Jiang, T., Lu, Y., He, Y., Tian, L. (2004). Regional homogeneity approach to fMRI data analysis. *Neuroimage*, 22(1), 394-400, doi:http://dx.doi.org/10.1016/j.neuroimage.2003.12.030. - Zang, Y.F., He, Y., Zhu, C.Z., Cao, Q.J., Sui, M.Q., Liang, M., Tian, L.X., Jiang, T.Z., Wang, Y.F. (2007). Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI. *Brain Dev*, 29(2), 83-91, doi:10.1016/j.braindev.2006.07.002. - Zou, Q.-H., Zhu, C.-Z., Yang, Y., Zuo, X.-N., Long, X.-Y., Cao, Q.-J., Wang, Y.-F., Zang, Y.-F. (2008). An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: Fractional ALFF. *Journal of Neuroscience Methods*, 172(1), 137-141, doi: http://dx.doi.org/10.1016/j.jneumeth.2008.04.012. - Zuo, X.-N., Xing, X.-X. (2014). Test-retest reliabilities of resting-state FMRI measurements in human brain functional connectomics: A systems neuroscience perspective. *Neuroscience & Biobehavioral Reviews*, 45, 100-118, doi:http://dx.doi.org/10.1016/j.neubiorev.2014.05.009. Best, Chao-Gan -- Chao-Gan YAN, Ph.D. Professor, Principal Investigator Director, International Big-Data Center for Depression Research Deputy Director, Magnetic Resonance Imaging Research Center Institute of Psychology, Chinese Academy of Sciences 16 Lincui Road, Chaoyang District, Beijing 100101, China - Initiator <http://rfmri.org/DPARSF>DPABI <http://rfmri.org/DPABI> <http://rfmri.org/DPARSF>, <http://dpabi.org>DPARSF <http://rfmri.org/DPARSF>, PRN <http://rfmri.org/PRN> and The R-fMRI Network <http://rfmri.org> (RFMRI.ORG <http://rfmri.org/>) http://rfmri.org/yan http://scholar.google.com/citations?user=lJQ9B58AAAAJ

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mri_glmfit: don't display "positive"
by Rockers, Elijah D. 23 Sep '19

23 Sep '19

External Email - Use Caution Hello, with Qdec, there was an option to "remove" positive (or negative) results from the displayed overlay... Is it possible to do something similar with the results of mri_glmfit, but displaying with freeview instead? For instance, if I wanted to exclude regions that appear to have increased cortical thickness when compared to healthy controls? Thanks, Eli Houston Methodist. Leading Medicine. Houston Methodist is ranked by U.S. News & World Report as the No. 1 hospital in Texas and among the top 20 hospitals nationwide. Houston Methodist is the only nationally ranked Honor Roll hospital in the state and is designated as a Magnet hospital for excellence in nursing. houstonmethodist.org | twitter.com/MethodistHosp | facebook.com/HoustonMethodist ***CONFIDENTIALITY NOTICE*** This e-mail is the property of Houston Methodist and/or its relevant affiliates and may contain restricted and privileged material for the sole use of the intended recipient(s). Any review, use, distribution or disclosure by others is strictly prohibited. If you are not the intended recipient (or authorized to receive for the recipient), please contact the sender and delete all copies of the message. Thank you.

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Keep manual edits of older freesurfer versions?
by Joëlle Ismay Rosanne Van Der Molen 23 Sep '19

23 Sep '19

External Email - Use Caution Dear FreeSurfer experts, I have a question regarding manual edits and change of FreeSurfer version. In our lab, we have thus far processed most of our T1 scans using FS version 5.1 and have performed manual edits when needed. We are now updating our processing to FS version 6.0, and would like to use previously edited data (from the 5.1 version) as an input for the FS version 6.0 processing (based on previous emails from the mail archive, I understand this makes sense?). Ideally, I'd like to store the FS6 outputs in a new parent directory (different from the directory where the FS5.1 processing outputs are stored). However, simply running: recon-all -s subject_name -sd /path/to/FS6_outputs/ -all ... with /path/to/FS5.1_outputs/ as a SUBJECTS_DIR doesn't work (it looks for input data in the -sd specified output directory, which doesn't contain anything yet). Adding an -i flag with a full path to the desired output directory also doesn't work: recon-all -s subject_name_FS6 -sd /path/to/FS6_outputs/ -i /path/to/FS5.1_outputs/subject_name/ ... as it says the -i flag needs a file as an input, not a folder. Now, adding an -i flag and giving for instance the 001.mgz as input works: recon-all -s subject_name_FS6 -sd /path/to/FS6_outputs/ -i /path/to/FS5.1_outputs/subject_name/mri/001.mgz However, if I am not mistaken, the manual edits are not stored in this 001.mgz file. Thus, does this mean that when rerunning a new version of freesurfer on already processed data, the same subject folder has to be used as input (FS 5.1 processed data) and output (FS 6 processing outputs)? And if so, should old files (that remain non-modified after the FS6 run) be removed? Thank you in advance for your answer, Best regards, Joëlle van der Molen

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GLM analysis question
by Ferraro, Pilar 23 Sep '19

23 Sep '19

External Email - Use Caution To the kind attention of the FreeSurfer team, I have some questions concerning a GLM analysis I’m running and any help would be greatly appreciated! I’m interested in identifying cortical regions where older age is associated with greater atrophy. However, unlike the example reported in the tutorial page, I do not have two groups (male and females) but just one group (patients, regardless of their gender). - Firstly, I’ve generated an “age.fsgd" file with the following structure: Class Main Variables Age Input subj 1 Main 61 Input subj 2 Main 73 …. And so on. - Secondly, I’ve assembled the data using the mris_preproc command (including resampling, concatenating and smoothing). - Thirdly, I’ve proceeded with the glm analysis using the mri_glm command. However, here I’ve changed the fsgd option, and in particular: —fsgd age.fsgd doss (I thought the DOSS design was more appropriate in my case). FIRST QUESTION: is this correct? Then, I’ve set the contrast in the "lh-Avg-thickness-age-Cor.mtx” file as: 0 1. SECOND QUESTION: is this correct? In this case I’ve set the intercept value as 0 and the slope value as 1. Many thanks for your help, Pilar

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talairach.m3z not found
by Dev vasu 23 Sep '19

23 Sep '19

External Email - Use Caution Dear all, When i run recon-all , i am encountering an error transforms/ talairach.m3z not found during registration phase, could some one please let me know how to resolve this?. Thanks Vasudev

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Fwd: Talairach Failure Dection error for recon-all
by Hang Zeng 23 Sep '19

23 Sep '19

External Email - Use Caution mT1.nii <https://drive.google.com/file/d/1ABR_hATWJP7QisH3TIw1_yZjVaxaucgn/view?usp=…> Dear Freesurfer users, I am trying to run the recon-all command for a T1 imge. The image is bias corrected using spm-segmentation (see attached). And the Talarich Failure Dection error occurred (see the log file). I ran the same analysis with the non-processed T1 and it worked. Any information would be appreciated Best, -- Hang ZENG Institute of Neuroscience and Medicine (INM-3) Forschungszentrum Juelich, Leo-Brandt-Str. 5 52425 Juelich Email: h.zeng(a)fz-juelich.de <zenghang14(a)gmail.com> & zenghang14(a)gmail.com Telefon: +49 2461/61-85328

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freeview command line options
by Rockers, Elijah D. 23 Sep '19

23 Sep '19

External Email - Use Caution Hello, it's possible I found a bug in freeview: I'm using the overlay_color option with freeview. Specifically I am trying to use both the "truncate" and "inverse" options in a command line call to freeview for a pipeline I am building. The documentation says that I can apply more than one, delimited by commas .... however I have found that if I attempt to use both truncate and inverse, it seems to be only applying whichever one appears last on the list. In an interactive instance of freeview, doing everything manually, I have no problems. Just seems to be an issue with the command line call. Any suggestions on how I might proceed in this case? -Eli Houston Methodist. Leading Medicine. Houston Methodist is ranked by U.S. News & World Report as the No. 1 hospital in Texas and among the top 20 hospitals nationwide. Houston Methodist is the only nationally ranked Honor Roll hospital in the state and is designated as a Magnet hospital for excellence in nursing. houstonmethodist.org | twitter.com/MethodistHosp | facebook.com/HoustonMethodist ***CONFIDENTIALITY NOTICE*** This e-mail is the property of Houston Methodist and/or its relevant affiliates and may contain restricted and privileged material for the sole use of the intended recipient(s). Any review, use, distribution or disclosure by others is strictly prohibited. If you are not the intended recipient (or authorized to receive for the recipient), please contact the sender and delete all copies of the message. Thank you.

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