Freesurfer March 2017

freesurfer@nmr.mgh.harvard.edu

148 participants
263 discussions

Pial in the thalamus
by Yann Quidé 15 Mar '17

15 Mar '17

Dear all, We have this issue around the thalamus that is recurring in several of our scans and there does not seem to be a problem with the white matter mask in that area. Is it a problem? Does anyone have an idea how to fix this? We are using Freesurfer v5.3. Thanks. Yann

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Postdoctoral Position -- Baby Brain Connectome
by gangli 15 Mar '17

15 Mar '17

Postdoctoral research associate and visiting student/scholar positions are available in the Department of Radiology and Biomedical Research Imaging Center (BRIC) at the University of North Carolina at Chapel Hill (UNC-Chapel Hill). Our current focuses are to better understand the dynamic development of brain structure, function and connectivity during critical early postnatal stages, via computational analysis of high-quality multimodal neuroimaging data, such as data acquired by UNC/UMN Baby Connectome Project. We are seeking highly motivated individuals who have extensive research experience in neuroimaging analysis (e.g., structural, diffusion or functional MRI) and demonstrated academic excellence, including publications in first-class journals and conferences. The postdoctoral candidate should have a Ph.D. (or equivalent) in Neuroscience, Computer Science, Applied Mathematics/Statistics, Electrical Engineering, Biomedical Engineering, or related fields. Good command of programming tools including Matlab, C++, Linux, and scripting are necessary to carry out the research work in this group. The candidate will support our efforts either in advancing neuroimaging analysis technologies or in neuroscience applications. The successful candidate will be part of a diverse group including neuroscientists, radiologists, psychologists, physicists, biostatistician, and computer scientists, and will build upon the group's extensive foundation on neuroimaging analysis. If interested, please email resume to Dr. Gang Li (gang_li(a)med.unc.edu)

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ROI analysis - smoothing
by Mihaela Stefan 15 Mar '17

15 Mar '17

Hello FreeSurfers, I would like to run a group analysis on cortical thickness using existing Desikan labels. When I run the command for smoothing, should I replace *--cortex* with *--label-trg*? In other words, for ROI analysis, should we smooth *only* the target mask? mri_surf2surf --hemi lh \ --s fsaverage \ --sval lh.gender_age.thickness.00.mgh \ --fwhm 10 \ * --cortex* \ --tval lh.gender_age.thickness.10B.mgh I followed the instructions from here: https://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/GroupAnalysis https://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/AnatomicalROI https://surfer.nmr.mgh.harvard.edu/fswiki/mri_glmfit http://freesurfer.net/fswiki/mri_surf2surf Thank you! Mihaela

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trouble with mri_convert and old dicom files
by Mark Lescroart 15 Mar '17

15 Mar '17

Hello, I'm trying to create a nifti file from some older (2006-2009) dicom files using mri_convert, and I'm having some difficulty. Part of this is uncertainty about the dicom files in question. The files were collected on Siemens scanner between 2006 and 2009, and I *believe* they should be in Siemens dicom format. They came off the magnet without a .dcm extension, if I recall correctly, but I used Brain Voyager to rename the dicom files (I believe all it does is re-title them to reflect the acquisition order, but I'm not 100% sure about that - that could be part of the problem). Running mri_convert to create a nifti file from the first file in each of the sequences I have yields the error I have copied below. <redacted> bits are there for anonymity, I don't think those fields relate to the problem. The main problem with this call seems to be that some fields regarding the image position are not read correctly, so the affine transform has nans in it. I also tried calling mri_convert -it dicom, which succeeded, but created an image that was of shape (384, 384, 1, 202). I don't know why that call to mri_convert doesn't correctly recognize that the images in the dicoms are, in fact, mosaic images (in the first call, there was an "IsMosaic" field that was set to 0, but I'm pretty sure it should be 1 or True or whatever); the resulting 4D array should be (64, 64, 32, 202). However, the image that the second call created may have had a correct affine transform (at least there were no nans) - to check on it in python, I called: nii = nibabel.load(file_name) nii.affine ... and got: array([[ -3.5 , -0. , -0. , 672.67797852], [ -0. , -3.5 , -0. , 690.59564209], [ 0. , 0. , 3. , -52.07869339], [ 0. , 0. , 0. , 1. ]]) ... So, now I'm a little stuck. -it seimens did not help, gave me the same error as below (same for -it siemens_dicom). I don't fully understand how to possibly override the bad info, or how to tell mri_convert where to find the correct info, or how to tell if I'm just out of luck with this whole endeavor. mri_convert --version spits out "stable5", which might be a slightly older version. Any help will be much appreciated. Cheers, Mark Error message: ---- Getting Series No Scanning Directory INFO: Found 993 files in old_data/ML_Localizers/Raw_Retinotopy_05_29_09 INFO: Scanning for Series Number 21 INFO: found 202 files in series INFO: loading series header info. # <there were lots of these error lines, one for each file in the series; i think these are due to the space between the subject ID, which I've redacted, and -0021-0001-00001.dcm > # error: /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeD efault.xctoolchain/usr/bin/strings: invalid decimal number in flag: -0021-0001-00001.dcm Usage: /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeD efault.xctoolchain/usr/bin/strings [-] [-a] [-o] [-t format] [-number] [-n number] [[-arch <arch_flag>] ...] [--] [file ...] WARNING: file <redacted> -0021-0001-00001.dcm does not contain a Siemens ASCII header has this file been anonymized? Proceeding as best as I can ... INFO: (384 384 1), nframes = 202, ismosaic=0 PE Dir COL COL FileName <redacted>/<redacted> -0021-0001-00001.dcm Identification NumarisVer syngo MR B15 ScannerModel TrioTim PatientName <redacted> Date and time StudyDate <redacted> StudyTime 105825.156000 SeriesTime 122023.890000 AcqTime 122021.700000 Acquisition parameters PulseSeq *epfid2d1_64 Protocol <redacted> PhEncDir COL EchoNo 1 FlipAngle 90 EchoTime 30 InversionTime -1 RepetitionTime 2000 PhEncFOV 0 ReadoutFOV 0 Image information RunNo 20 SeriesNo 21 ImageNo 1 NImageRows 384 NImageCols 384 NFrames 202 SliceArraylSize 0 IsMosaic 0 ImgPos 672.6780 690.5956 -52.0787 VolRes 3.5000 3.5000 3.0000 VolDim 384 384 1 Vc -1.0000 -0.0000 0.0000 Vr -0.0000 -1.0000 0.0000 Vs nan nan nan VolCenter nan nan nan TransferSyntaxUID 1.2.840.10008.1.2.1 UseSliceScaleFactor 0 (slice 0: 1) INFO: no Siemens slice order reversal detected (good!). TR=2000.00, TE=30.00, TI=-1.00, flip angle=90.00 i_ras = (-1, -0, 0) j_ras = (-0, -1, 0) k_ras = (nan, nan, nan) Reslicing using trilinear interpolation MRIresample(): error inverting matrix; determinant is nan, matrix is: -3.500 -0.000 nan nan; -0.000 -3.500 nan nan; 0.000 0.000 nan nan; 0.000 0.000 0.000 1.000;

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MNI 305 atlas
by Fotiadis, Panagiotis 15 Mar '17

15 Mar '17

Hi FS team, I was wondering whether you know where I can find the MNI305 altas (with labels that correspond to cortical/subcortical parcellations). I have found the average MNI305 brain under the $FREESURFER_HOME directory, but if I'm not mistaken this is just the average brain and not the labeled one. Thanks in advance, Panos Panagiotis Fotiadis Research Technologist II J. P. Kistler Stroke Research Center Massachusetts General Hospital 175 Cambridge Street, Suite 300 Boston, MA, 02114 T: (617) 643-3869

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MEG time series to surface overlay
by Dorothy Sincasto 15 Mar '17

15 Mar '17

Hi, I have MEG time series for every vertex in a decimated surface (~6000 vertices). I want to create a file (i think is called overlay) in which the timeseries are saved, like an fMRI mgz overlay. How can I do that with matlab? I have tried read_surf for reading the midthickness surface file, and then using the vertex coordinates and the MEG time series variable as input for write_wfile. however i get the error: Error using bitshift Double inputs must have integer values in the range of ASSUMEDTYPE. Error in fwrite3 (line 26) b1 = bitand(bitshift(val, -16), 255) ; Error in write_wfile (line 58) fwrite3(fid, v(i)) ; % vertex number (0-based) It seems that's not the function I need to use. Thanks Dorothy

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HCP Course 2017: Accommodations Reservations now available
by Jennifer Elam 15 Mar '17

15 Mar '17

Spaces are beginning to fill for the 2017 HCP Course: "Exploring the Human Connectome" <https://store.humanconnectome.org/courses/2017/exploring-the-human-connecto…>, to be held June 19-23 at the Djavad Mowafagian Centre for Brain Health <http://www.brain.ubc.ca/> at University of British Columbia (UBC) in Vancouver, BC, Canada! Reservations for on-site accommodations <https://store.humanconnectome.org/courses/2017/exploring-the-human-connecto…> for those attending the course are now available. The 5-day intensive HCP course will provide training in acquisition, processing, analysis and visualization of whole brain imaging and behavioral data using methods and software tools developed by the WU-Minn-Oxford Human Connectome Project (HCP) consortium. The HCP Course is the best place to learn directly from HCP investigators and to explore HCP data and methods. This year's course will cover where HCP is heading with advent of the Lifespan HCP development (ages 5-18) and aging (ages 35-90+) projects and will provide hands-on experience in working with the multi-modal human cortical parcellation (Glasser *et al.* 2016, Nature <http://www.ncbi.nlm.nih.gov/pubmed/27437579> <http://www.ncbi.nlm.nih.gov/pubmed/27437579>) and with the “HCP-Style” paradigm for data acquisition, analysis, and sharing (Glasser *et al.* 2016, Nature Neuroscience <https://www.ncbi.nlm.nih.gov/pubmed/27571196>). For more info and to register visit the HCP Course 2017 website <https://store.humanconnectome.org/courses/2017/exploring-the-human-connecto…>. If you have any questions, please contact us at: hcpcourse@humanconnectome. org We look forward to seeing you in Vancouver! Best, 2017 HCP Course Staff

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Question about Paired Analysis
by Maaike van der Plas 15 Mar '17

15 Mar '17

Dear Experts, We're doing a study on a group of patients with the same disease, all of whom got the same treatment for three months. Some of them improved (thus becoming "responders"), others didn't ("non-responders"). They got MRI's at baseline (tp1: before the treatment) and again afterwards (tp2). All subjects received both MRI's and the interval between MRI's was three months for everyone. Our goal is to see what changed in the brains of the responders and the non-responders from tp1 to tp2. Specifically, we want to compare the responders at tp2 to responders at tp1, non-responders at tp2 to non-responders at tp1 and we want to compare the change in responders to the change in non-responders. We'd like to create one GLM in which we can do all three of these analyses. To do so, we're currently using the tutorial on Paired Analysis ( http://surfer.nmr.mgh.harvard.edu/fswiki/PairedAnalysis) with two groups (non-responders and responders), and two covariates (age and gender). My first question is about the first FSGD file, containing the matching pairs listed consecutively. Should these subject names refer to the directories we got from the longitudinal processing stream (e.g. OAS2_001_MRI.long.OAS2_001) or those we got from running the 'normal', non-longitudinal recon-all command (e.g. OAS2_001_MRI)? My second question is about the contrast file we should use to compare the subjects from tp2 to tp1 in each group separately. In the mailing list and in the tutorials, I'm mostly seeing examples to compare two groups with each other (with contrasts like '1 -1 0 0 0 0). But am I correct in thinking that to compare responders (the second group listed in the second FSGD file) at tp2 to tp1 while adjusting for gender and age, I should use the following contrast?: 0 1 0 0 0 0 Kind regards and thank you, M.C. van der Plas Leiden University Medical Center

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Re: [Freesurfer] Faulty alignment to standard surface
by Daan Wesselink 15 Mar '17

15 Mar '17

Dear Bruce, Thank you for your help! This did the trick. Kind regards, Daan --------- Message: 4 Date: Tue, 14 Mar 2017 10:58:13 -0400 (EDT) From: Bruce Fischl <fischl(a)nmr.mgh.harvard.edu> Subject: Re: [Freesurfer] Faulty alignment to standard surface To: Freesurfer support list <freesurfer(a)nmr.mgh.harvard.edu> Message-ID: <alpine.LRH.2.20.1703141054510.10321(a)door.nmr.mgh.harvard.edu> Content-Type: text/plain; charset="utf-8" HI Daan wow, that is a pretty unusual folding pattern, which I'm sure is the source of the issue. Are you sure which one is the central sulcus? If so, draw it (I guess using tksurfer as the current version of freeview doesn't have extensive surface drawing tools yet), probably by just "custom filling" the sulc, then rerun mris_register using the flag: mris_register --help | grep "-L" Usage: grep [OPTION]... PATTERN [FILE]... Try 'grep --help' for more information. tiamat [C2.3T.recon] mris_register --help | grep "\-L" -L <labelfile atlas_gcsa_file label_name> where label_name is the exact name of the central sulcus label in the gcsa file you use, and can be obtained by looking in our color lookup table file such as FreeSurferColorLUT.txt, or just running mris_info on the gcsa file you are using (they are all in $FREESURFER_HOME/average). cheers Bruce On Tue, 14 Mar 2017, Daan Wesselink wrote: > Dear Douglas, > > Thank you for your response. The surface placement on the individual seems > correct (see?https://ibb.co/f4aeAa ). However, if I load the annotation > files, the labels are wrong. In this screenshot (https://ibb.co/cycFiv ), > I've loaded the BA annotation outlines and BA3a in yellow on the left > hemisphere. It seems to think the wrong fold is the central sulcus. > > Thanks, > > Daan? > > Message: 7 > Date: Sun, 12 Mar 2017 19:00:21 -0400 > From: Douglas Greve <greve(a)nmr.mgh.harvard.edu> > Subject: Re: [Freesurfer] Faulty alignment to standard surface > To: freesurfer(a)nmr.mgh.harvard.edu > Message-ID: > <7ab364ef-539f-fd65-4346-db68d915ca05(a)nmr.mgh.harvard.edu> > Content-Type: text/plain; charset="windows-1252" > > not sure what you mean. Can you send a pic? Is the surface > placement on > the individual correct (ie, are the white and pial surfaces > properly > placed on the T1)? > > > On 3/10/17 11:19 AM, Daan Wesselink wrote: > > Dear experts, > > > > I've run the standard recon-all pipeline on a subject, for > whom the > > log does not report any errors and the white and pial surface > follow > > the structural nicely. However, the coregistration to the > standard > > surface has gone wrong: it seems like the central sulcus (e.g. > labels > > BA1, BA3a) is placed on top of the postcentral sulcus. > > > > Does someone know how to fix this problem and/or better > identify the > > step where it went wrong? > > > > Many thanks, > > > > Daan Wesselink > > > > > > _______________________________________________ > > Freesurfer mailing list > > Freesurfer(a)nmr.mgh.harvard.edu > > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > > > On 14 March 2017 at 15:50, freesurfer-request(a)nmr.mgh.harvard.edu < freesurfer-request(a)nmr.mgh.harvard.edu> wrote: > Send Freesurfer mailing list submissions to > freesurfer(a)nmr.mgh.harvard.edu > > To subscribe or unsubscribe via the World Wide Web, visit > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > or, via email, send a message with subject or body 'help' to > freesurfer-request(a)nmr.mgh.harvard.edu > > You can reach the person managing the list at > freesurfer-owner(a)nmr.mgh.harvard.edu > > When replying, please edit your Subject line so it is more specific > than "Re: Contents of Freesurfer digest..." > > > Today's Topics: > > 1. Whole preprocessing with FAST without to perform a seed based > analysis (stdp82(a)virgilio.it) > 2. Re: Brain to skull distance (Bruce Fischl) > 3. Re: Ventricles not filled (Bruce Fischl) > 4. Re: Faulty alignment to standard surface (Bruce Fischl) > 5. Re: tkmedit error (Bruce Fischl) > 6. Re: fsgd 4 groups, continuous dependent variable, 2 > covariates (Douglas Greve) > 7. Re: Whole preprocessing with FAST without to perform a seed > based analysis (Douglas Greve) > 8. Re: mri_vol2surf (Redwan Maatoug) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Tue, 14 Mar 2017 15:45:17 +0100 (CET) > From: <stdp82(a)virgilio.it> > Subject: [Freesurfer] Whole preprocessing with FAST without to perform > a seed based analysis > To: freesurfer(a)nmr.mgh.harvard.edu > Message-ID: > <1222513272.4869241489502717860.JavaMail.httpd@fep-webmail-05> > Content-Type: text/plain; charset="utf-8" > > Hi list,in FS-FAST, on rs-fMRI data, is possible to run selxavg3-sess > without -a option?I would use whole the FS-FAST to preprocess my data. I > would include the mkanalysis-sess step but I would not perform a seed-based > analysis. ThanksStefano >

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Postdoc position at the University of Pennsylvania
by Laura Wisse 15 Mar '17

15 Mar '17

The Penn Memory Center (PMC; http://pennmemorycenter.org) and Penn Computing and Science Laboratory (PICSL; http://picsl.upenn.edu) is seeking candidates for a Postdoctoral Fellow position to study structural and functional alterations of the medial temporal lobe (MTL) associated with aging and preclinical Alzheimer’s Disease. The Postdoctoral Fellow will support NIH-funded collaborative projects of Drs. David Wolk and Paul Yushkevich, utilizing and developing advanced morphometric image analysis methods with a focus on MTL subregions. We are interested in the interaction and consequences of normal aging, vascular disease, and molecular markers of Alzheimer’s Disease on MTL structure and function. Multimodal imaging, including 3T/7T MRI, fMRI, Amyloid PET, and Tau PET will be employed along with experimental memory measures. The successful candidate will have completed a PhD in neuroscience, psychology, biomedical engineering, or an equivalent field, have proven technical ability in image analysis, and a demonstrated publication record. Background knowledge in memory, cognitive neuroscience of aging/Alzheimers Disease, MTL segmentation, scripting languages, and behavioral statistical analyses are highly desirable. The Postdoctoral Fellow will have opportunities for first-author papers in competitive conferences and/or leading journals in their respective fields. Primary responsibilities in this position include the analysis, interpretation, and scientific presentation of structural and functional MRI and behavioral data related to ongoing projects of MTL subregional structure and function. The University of Pennsylvania is a leading center in human brain imaging and neurodegeneration, with access to advanced MRI and PET imaging. The PMC is home to the Clinical Core of the NIH-funded Penn Alzheimer’s Disease Core Center of which Dr. Wolk is Associate-Director. PICSL is a dynamic and growing group in the Department of Radiology that is involved in many exciting biomedical imaging projects, including multi-modality neuroimaging, animal imaging, geometric and statistical modeling of imaging data, diffeomorphic registration and multi atlas segmentation. We are particularly well known for our open-source research software, such as ITK-SNAP and ANTS. The Wolk and Yushkevich laboratories moved to newly renovated space in the Richards/Goddard ( https://en.wikipedia.org/wiki/Richards_Medical_Research_Laboratories) building, a designated National Historic Landmark designed by the renowned architect Louis Kahn. Virtually all neuroimaging and brain function research groups at Penn are housed in this complex, including the Center for Cognitive Neuroscience (CCN; http://ccn.upenn.edu) Although the Penn campus is already very compact, consolidating the many faculty members involved in neuroimaging facilitates broader participation in projects, seminars, workshops, and interdisciplinary training, and will provide an outstanding environment for trainees to interact with faculty and with each other. The University of Pennsylvania is located in Philadelphia, a vibrant city that offers many professional and cultural opportunities. The campus is in walking distance from the city center, which has experienced enormous growth and transformation in the last two decades. Philadelphia is famous for its history, independent arts, music, and theatre, and a rich food scene. It is one of the few major cities in the United States that is affordable for academic trainees, both in urban and suburban settings. The Philadelphia region has an excellent public transportation system that connects many distinctive urban and suburban communities. Some of the best schools in the state are located in the Philadelphia region. New York City, Washington DC, New Jersey beaches and Pocono Mountains are within 2-3 hours by car, bus, or train. The University of Pennsylvania is an equal opportunity, affirmative action employer. Women and minority candidates are strongly encouraged to apply. Informal inquiries can be directed to David Wolk (david.wolk(a)uphs.upenn.edu)

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Freesurfer March 2017