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30084 discussions

searchable Destrieux atlas by recon all labels?
by Andrea Bozoki 11 Jan '16

11 Jan '16

Is there any interactive or searchable version of the Destrieux atlas parcellations (the ones used by aparc.a2009s.annot)? It would be very helpful to be able to toggle back and forth between individual recon-all labels and a color atlas of the relevant region when examining ROI-based quantitative output (output that is not visual). Thanks, Andrea B.

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BA46 volume from rostral mid-frontal gyrus
by Jae Cho 11 Jan '16

11 Jan '16

Dear FreeSurfer Experts, Could someone help me with a pipeline for creating a label from an edited existing label? I have aligned the aparc+aseg and its respective orig into ac-pc plane using AFNI. I then used fslmaths to make an ROI of just the rh_mid-frontal-gyrus. After editing the ROI using freeview, I am having trouble identifying which commands to use in order to create a new label and extracting the volume. Thank you, Jae

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About the pdf_gamma function in fsfast's toolbox
by LiTuX Sol 11 Jan '16

11 Jan '16

Hi, I’m working on some fMRI data processing these days. In order to construct a HRF, I find this Matlab function in fsfast. But after some careful comparison, it seems that the gamma pdf in this function is not consistent with FSL’s version, and differs from the standard gamma pdf. So perhaps it is a typo in your code? In this function, the gamma pdf is written as: > pdfx = (b.^2) .* (…); But comparing to FSL’s feat_model.cc, I think this term should be > pdfx = (b.^a) .*(…); Which will be consistent with the original gamma pdf from Wikipedia. Thanks for your nice software and thanks for your attention. 😊 Su, --- >From Beijing Normal University.

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Question about Intracranial Volume
by pietro de rossi 11 Jan '16

11 Jan '16

Dear FreeSurfers, I am editing a paper on subcortical volumes in deficit schizophrenia after some reviewers' comments. On of them suggested me to correct the volumes of subcortical structures for whole brain volume instead of intracranial volume. In the reviewer's opinion ICV estimated by FreeSurfer 5.1 has a bad quality and is not reliable. However, neither the reviewer provides any evidence, nor I could find any... Is there any evidence for this? Thanks in advance, Pietro -- Pietro De Rossi, MD ------------------------------------- Sapienza Università di Roma, Facoltà di Medicina e Psicologia, Dipartimento NESMOS (Neuroscienze, Salute Mentale, Organi di Senso), Ospedale Sant'Andrea, Via di Grottarossa 1035-1039, 00189 Roma NESMOS Department (Neurosciences, Mental Health and Sensory Functions), School of Medicine and Psychology, Sapienza University, Sant’Andrea Hospital, Via di Grottarossa 1035-1039, 00189 Rome, Italy Laboratorio di Neuropsichiatria, Dipartimento di Neurologia Clinica e Comportamentale, IRCCS Fondazione Santa Lucia, via Ardeatina 306 - 00179 Roma Tel. +39 (0)6 51501358 Fax +39 (0)6 90280774 web: http://www.neuropsichiatrialab.com

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Hippocampal Subfields (6.0) Error
by Andrew Schoen 11 Jan '16

11 Jan '16

Hi all, We are running some hippocampal subfield segmentations for two independent studies. They have already been processed through the standard pipeline (5.3), so I was just running the following command: *recon-all -s ${subjectid} -hippocampal-subfields-T1* For both test cases, the processing seems to have halted (no more updates to the log file), but the command keeps running. For one study, it trailed off here: ************************************************************************************************************************ Resolution level 1 iteration 2 deformation iterations 13 Number of Meshes: 1 Using CG optimizer Did one deformation step of max. 0.00037944 voxels in 14.6033 seconds minLogLikelihoodTimesPrior = 2.3442e+06 Resolution level 1 iteration 2 deformation iterations 14 Number of Meshes: 1 Using CG optimizer Did one deformation step of max. 1.3541e-06 voxels in 3.5131 seconds minLogLikelihoodTimesPrior = 2.3442e+06 Resolution level 1 iteration 2 deformation iterations 15 Number of Meshes: 1 Using CG optimizer Did one deformation step of max. 0 voxels in 30.0807 seconds minLogLikelihoodTimesPrior = 2.3442e+06 maximalDeformation is too small; stopping Iteration 3 of 7 (eof) ************************************************************************************************************************ and the other here: ************************************************************************************************************************ Making Left-Accumbens-area map to reduced label 13 -------------- Making Unknown map to reduced label 14 Computing hyperparameters for estimation of Gaussians parameters Estimating typical intensities of molecular layer and alveus For ML in T1, we assume gray with high N In T2, we actually assume the same hypermean Smoothing mesh collection with kernel size 1.500000 ...Smoothing class: 0 Smoothing class: 1 Smoothing class: 2 Smoothing class: 3 Smoothing class: 4 Smoothing class: 5 Smoothing class: 6 Smoothing class: 7 Smoothing class: 8 Smoothing class: 9 Smoothing class: 10 Smoothing class: 11 Smoothing class: 12 Smoothing class: 13 done numberOfImages = 2 Image: 0 Image: 2 Iteration 1 of 7 (eof) ************************************************************************************************************************ Interestingly, for one study, we have T2-weighted images, and when I ran with that (same subject as second log, above), it ran to completion fine. Any idea what might be happening? Let me know if any other info would be useful! Thanks! Andrew Schoen Center for Healthy Minds Waisman Center University of Wisconsin - Madison

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Unknown cortical parcellation in S_calcarine (lh.aparc.a2009s.annot)
by Matthieu Vanhoutte 11 Jan '16

11 Jan '16

Dear FS's experts, Projecting volumic data onto native surface (brain mask: "Unknown_S_calcarine_ROI_mask.jpg"), I observed that a thin region in the S_calcarine was set to 0. I loaded then the inflated left surface and the l.aparc.a2009s.annot ("Unknown_S_calcarine_ROI_annot.jpg") and took into account that this region inside the S_calcarine was set as "unknown" in the parcellation file . So I checked the aseg at the anterior end of the calcarine and see if it incorrectly labeled some voxels there as ventricle. I corrected the aseg and rerun from there with this command : *recon-all -all -sd ${SUBJECTS_DIR} -subjid ${SUBJECT_ID} -nuintensitycor-3T -make all* However, this command exited with errors (please find attached recon-all_log.txt). Thanks in advance far any helping ! Best regards, Matthieu 2016-01-08 10:14 GMT+01:00 Matthieu Vanhoutte <matthieuvanhoutte(a)gmail.com>: > Hi Bruce, > > I erased the false ventricle signal and re-run with -make all option. > > However, Recon-all exited with errors: > > --------------------------------------------------- >> #@# 1/1 Hallaert_Beatrice_M0_2010-12-15 Thu Jan 7 19:46:56 CET 2016 >> -------------- >> ----------------------- >> mri_surf2surf --srcsubject Hallaert_Beatrice_M0_2010-12-15 --srchemi lh >> --srcsurfreg sphere.reg --trgsubject fsaverage --trghemi lh --trgsurfreg >> sphere.reg --tval >> ./tmp.mris_preproc.16394/Hallaert_Beatrice_M0_2010-12-15.1.mgh --sval >> /NAS/tupac/matthieu/FS5.3/Hallaert_Beatrice_M0_2010-12-15/surf/lh.volume >> --jac --sfmt curv --noreshape --no-cortex >> Source registration surface changed to sphere.reg >> Target registration surface changed to sphere.reg >> srcsubject = Hallaert_Beatrice_M0_2010-12-15 >> srcval = >> /NAS/tupac/matthieu/FS5.3/Hallaert_Beatrice_M0_2010-12-15/surf/lh.volume >> srctype = curv >> trgsubject = fsaverage >> trgval = >> ./tmp.mris_preproc.16394/Hallaert_Beatrice_M0_2010-12-15.1.mgh >> trgtype = >> srcsurfreg = sphere.reg >> trgsurfreg = sphere.reg >> srchemi = lh >> trghemi = lh >> frame = 0 >> fwhm-in = 0 >> fwhm-out = 0 >> label-src = (null) >> label-trg = (null) >> OKToRevFaceOrder = 1 >> Reading source surface reg >> /NAS/tupac/matthieu/FS5.3/Hallaert_Beatrice_M0_2010-12-15/surf/lh.sphere.reg >> Loading source data >> Reading curvature file >> /NAS/tupac/matthieu/FS5.3/Hallaert_Beatrice_M0_2010-12-15/surf/lh.volume >> ERROR: number of vertices in >> /NAS/tupac/matthieu/FS5.3/Hallaert_Beatrice_M0_2010-12-15/surf/lh.volume >> does not match surface (124822,125094) >> ERROR: reading curvature file >> Linux toto 3.13.0-24-generic #47-Ubuntu SMP Fri May 2 23:30:00 UTC 2014 >> x86_64 x86_64 x86_64 GNU/Linux >> >> recon-all -s Hallaert_Beatrice_M0_2010-12-15 exited with ERRORS at Thu >> Jan 7 19:46:57 CET 2016 >> > > Please find attached the logs. > > Moreover, I visualized aparc.a2009.annot and there's still unknown label > in calcarine. > > Best regards, > Matthieu > > > 2016-01-07 17:52 GMT+01:00 Matthieu Vanhoutte <matthieuvanhoutte(a)gmail.com > >: > >> Hi Bruce, >> >> Thank you I erased false ventricle and rerun recon-all with option -make >> all. >> >> Is there any mean to prevent this problem ? >> >> Best regards, >> Matthieu >> >> ------------------------------------- >> Matthieu Vanhoutte, MSc >> Research Engineer - Department of Neuroradiology >> Regional University Hospital, Lille, France >> http://www.ci2c.fr >> >> 2016-01-07 16:21 GMT+01:00 Bruce Fischl <fischl(a)nmr.mgh.harvard.edu>: >> >>> it's the bit of ventricle at e.g. 150, 117, 76 in the aseg. This should >>> be unknown instead. You can erase it all from the aseg.mgz, then rerun >>> recon-all -make all I think >>> >>> Bruce >>> On Thu, 7 Jan 2016, matthieuvanhoutte(a)gmail.com wrote: >>> >>> Matthieu (matthieuvanhoutte(a)gmail.com) has uploaded some files for you >>>> at the Martinos Center FileDrop: >>>> >>>> + T1.mgz (3.89 MiB) < >>>> http://gate.nmr.mgh.harvard.edu/filedrop2/?u=83wgnvpqp7q&f=1qg3sxihniv> >>>> + aseg.mgz (230.42 KiB) < >>>> http://gate.nmr.mgh.harvard.edu/filedrop2/?u=83wgnvpqp7q&f=41rb99vxdza> >>>> + aparc.a2009s+aseg.mgz (406.09 KiB) < >>>> http://gate.nmr.mgh.harvard.edu/filedrop2/?u=83wgnvpqp7q&f=b68kofegemp> >>>> >>>> Also, they left this message for you: >>>> Hi Bruce, >>>> >>>> I couldn't see what you've explained to me. I attached the T1 and aseg >>>> files, could you please give me coordinates of this phenomen ? >>>> >>>> Once problem have been seen, what is the process to follow for >>>> correcting aseg labels and re-run recon-all at which step ? >>>> >>>> Thanks in advance ! >>>> >>>> Best regards, >>>> Matthieu >>>> >>>> >>>> Hi Matthieu >>>> >>>> check the aseg at the anterior end of the calcarine and see if it >>>> incorrectly labels some voxels there as ventricle. The bit of WM that >>>> separates ventricle from calcarine at the posterior horn of the >>>> ventricle >>>> is thin and sometimes quite dark, and if we lose that the ventricle >>>> label >>>> can extend incorrectly into calcarine, in which case we think it isn't >>>> cortex. If you correct the aseg and rerun from there it should fix it. >>>> >>>> cheers >>>> Bruce >>>> >>>> >>>> On Thu, 7 Jan 2016, >>>> Matthieu Vanhoutte wrote: >>>> >>>> Dear FS's experts, >>>>> >>>>> Projecting volumic data onto native surface (brain mask: >>>>> "Unknown_S_calcarine_ROI_mask.jpg"), I observed that a thin region in >>>>> the >>>>> S_calcarine was set to 0. >>>>> >>>>> I loaded then the inflated left surface and the l.aparc.a2009s.annot >>>>> ("Unknown_S_calcarine_ROI_annot.jpg") and took into account that this >>>>> region >>>>> inside the S_calcarine was set as "unknown" in the parcellation file . >>>>> >>>>> What does it mean and is this possible to correct for this ? >>>>> >>>>> Best regards, >>>>> Matthieu >>>>> >>>> >>>> Please be aware, your upload will expire on December 31st. If you'd >>>> like to download these files, feel free to use the link below: >>>> >>>> http://gate.nmr.mgh.harvard.edu/filedrop2/?u=83wgnvpqp7q >>>> >>>> Cheers, >>>> The Martinos Center Web Team >>>> >>>> >>>> >>>> >>> >>> The information in this e-mail is intended only for the person to whom >>> it is >>> addressed. If you believe this e-mail was sent to you in error and the >>> e-mail >>> contains patient information, please contact the Partners Compliance >>> HelpLine at >>> http://www.partners.org/complianceline . If the e-mail was sent to you >>> in error >>> but does not contain patient information, please contact the sender and >>> properly >>> dispose of the e-mail. >>> >>> >> >

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Postdoctoral positions available -- San Diego
by Ruth Carper 08 Jan '16

08 Jan '16

The Brain Development Imaging Laboratory (BDIL) at the Dept.of Psychology, San Diego State University (SDSU), is offering 1-2 postdoctoralpositions in diffusion-weighted and other anatomical MRI techniques. Job Description Post-doctoral positions will be supported by several newlyfunded NIH projects examining brain structure and network organization acrossthe lifespan in autism spectrum disorders (ASD) including a study of toddlersand a study of older adults. New projects will implement multi-shell diffusionweighted imaging (i.e. multiple b-values, appropriate for calculation of ODFs, tractography,examination of neurite density in gray and white matter), multi-modalneuroanatomical imaging (e.g. combined T1, T2, DWI), and simultaneousmulti-slice fMRI. The postdoctoral scholar will be responsible for implementationof new analysis pipelines for diffusion weighted and/or anatomical MRI incollaboration with faculty and support staff, for assessment and mitigation ofartifacts, and for continuing analysis of our existing database of multimodalMRI data. Fellow will assist in supervision/training of graduate students andresearch assistants and in the preparation of manuscripts for publication. Thepostdoctoral fellow will regularly interact with collaborating faculty and willhave access to the rich San Diego Neuroscience and Cognitive Sciencecommunities. Requirements · PhD in Neuroscience, CognitiveScience, Psychology, Biomedical Engineering, or other relevant field. · Experience in data acquisition, preprocessing,and analysis of MRI data, with particular focus on diffusion and/or anatomicalMRI. · Preference will be given toapplicants with: o Experiencewith multiple analysis methods/toolkits in the relevant modality. o Experiencein multiple imaging modalities (e.g. both diffusion and functional imaging). o Experiencewith ASD, other developmental disorders, or normal aging. Brain Development Imaging Lab &Research Facilities BDIL (www.sci.sdsu.edu/bdil)is a diverse and collaborative research group with 3 faculty members andmultiple PhD and Master’s students in Psychology, Cognitive Science, ClinicalPsychology, and BioInformatics from both SDSU and University of California, SanDiego (UCSD). Research applies multiple imaging modalities (e.g. DWI,anatomical MRI, fMRI, functional connectivity MRI, MR spectroscopy) as well asbehavioral and neuropsychological measures to investigate the brain bases ofASD and age-related change across the lifespan (1-65 years). BDIL collaborateswith experts in MR physics, Radiology, EEG, MEG, and Bioinformatics toimplement innovative imaging and analysis techniques (e.g., simultaneousfMR/EEG recording, combined MEG and MRI). BDIL maintains close ties withfaculty at UCSD Center for Functional MRI (CFMRI) where imaging is performed andwith affiliated faculty at UCSD School of Medicine. BDIL researchers have fullaccess to CFMRI (http://fmri.ucsd.edu/),a research dedicated facility with two 3T human research scanners (8 & 32channel head coils), led by top experts in radiology physics, and supported byengineering staff. To Apply Please e-mail CV, research statement, reprints, and 3 lettersof recommendation to Ralph-Axel Mueller at: rmueller(a)sdsu.edu.

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amygdala nuclear subregions
by Dorit Kliemann 08 Jan '16

08 Jan '16

Hi Heidi, segmentation of amygdalar subregions is currently not yet implemented in FreeSurfer, but we are working on including this feature soon. Best, Dorit ----------------------------- Message: 9 Date: Fri, 8 Jan 2016 13:21:48 +0000 From: "Jacobs H (NP)" <h.jacobs(a)maastrichtuniversity.nl> Subject: [Freesurfer] amygdala nuclear subregions To: Freesurfer support list <freesurfer(a)nmr.mgh.harvard.edu> Message-ID: <D2B5767A.155A7%h.jacobs(a)maastrichtuniversity.nl> Content-Type: text/plain; charset="iso-8859-1" Dear FreeSurfer developers, In the FreeSurferColorLut file I see labels for the subregions of the amygdala. Is it possible to extract the volumes for these regions? And how can I do this? I don't see them in the aseg or aparc stat files. Many thanks! Heidi

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Gray Matter Errors, Ignored Areas
by Julio Alberto González Torre 08 Jan '16

08 Jan '16

Hi everyone. I have a little trouble. First of all, I performed the recommended reconstruction. When I inspect the results, the boundaries of white matter are correct, but the Gray Matter is incorrectly understimated. As I show in the attached file, large parts of gray matter were ignored on the pial surface. It is extrange, because when I inspect the aseg file, the voxels of those areas are correct classified as cortex. I have been searching how to fix it, but I was unable to find how to do it on the troubleshooting tutorials. When this problem appears in white matter tissue, can be corrected with control points. What can I do when the same problem is in gray matter? Thanks.[image: Imágenes integradas 1]

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Re: [Freesurfer] malloc error with mri_glmfit-sim
by Antonin Skoch 08 Jan '16

08 Jan '16

Dear FreeSurfer experts, I am getting the same error with malloc(): memory corruption on mri_segstats invoked within mri_glmfit-sim. Apart from Frances, the process continues forever without any output after error message (i.e. without "Writing to..." and "Abort..." line). My commandline is: mri_glmfit-sim --glmdir . --cache 2 abs --cwp 0.05 --2spaces My version is also v5.3.0, Ubuntu, 32bit. With some data or some parameters of --cache it works OK. I do not get this error at 64bit version with the data and parameters which caused the error in 32bit version. Here is full relevant output of mri_segstats. $Id: mri_segstats.c,v 1.75.2.9 2013/02/16 00:09:33 greve Exp $ cwd cmdline mri_segstats --seg ./lh-diff-C-PL-intercept-pial_lgi/cache.th20.abs.sig.ocn.mgh --exclude 0 --i /dataStrojovna2_1/ansk/ADHD/cortical/C_PN_PL_porovnani/qdec/pial_lgi_5_lh_dg_age/y.mgh --avgwf ./lh-diff-C-PL-intercept-pial_lgi/cache.th20.abs.y.ocn.dat --sum /tmp/mri_glmfit-sim.junk.8273 sysname Linux hostname aglaia4 machine i686 user ansk UseRobust 0 Loading ./lh-diff-C-PL-intercept-pial_lgi/cache.th20.abs.sig.ocn.mgh Loading /dataStrojovna2_1/ansk/ADHD/cortical/C_PN_PL_porovnani/qdec/pial_lgi_5_lh_dg_age/y.mgh Voxel Volume is 1 mm^3 Generating list of segmentation ids Found 4 segmentations Computing statistics for each segmentation 1 1 2542 2542.000 2 2 2426 2426.000 3 3 1738 1738.000 Reporting on 3 segmentations Computing spatial average of each frame 0 1 2*** glibc detected *** mri_segstats: malloc(): memory corruption: 0x2f80d4b0 *** Regards, Antonin Skoch

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