Freesurfer

freesurfer@nmr.mgh.harvard.edu

4 participants
30090 discussions

Matrix building
by Linn Mittlestein 25 Jun '13

25 Jun '13

Hello, I wondering if possible using fsgd files to do group analysis with two factors (one with 3 levels, one with 2 levels), with one covariate. On fsgd example list I cannot find this example? Kind Regards, Linn

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Re: [Freesurfer] ribbon label volume mapping
by Colin Reveley 25 Jun '13

25 Jun '13

Doug - thanks that sounds well worth trying. the labels we have have arbitrary spatial resolution in the saggital plane, and 1mm gaps between saggital slices. In general in this project we are using an isotropic resolution of 0.25mm. To generate surfaces in freesurfer I have to downsample to 0.35mm (to fit into 256) in applying the procedure you suggest a) is it possible to use a volume with a dimension > 256? b) is it possible to use a non-isotropic resolution? playing around with non-isotropic resolutions, projection fractions and vote would yield different results. c) can mri_aparc2aseg output a volume > 256? 0.35 isotropic will be ok. we'd prefer 0.25 if we can. best Colin > ---------- Forwarded message ---------- > From: Douglas Greve <greve(a)nmr.mgh.harvard.edu> > To: <freesurfer(a)nmr.mgh.harvard.edu> > Cc: > Date: Sun, 23 Jun 2013 20:03:09 -0700 > Subject: Re: [Freesurfer] ribbon label volume mapping > > You could run mri_vol2surf at different projection fractions (and using > nearest neighbor interp). This will create a set of files, one for each > projection fraction. You can then run mri_concat with the --vote option to > get you the most frequently occurring label. You could then use > mris_seg2annot to create an annotation. > > If you want to go the other way, you will need to combine your labels into > an annotation (mris_label2annot), then convert that into a volume with > mri_aparc2aseg. > > doug > > > On 6/22/13 10:08 AM, Colin Reveley wrote: > > If one has a volume of integers, each representing a cortical area, > can one map that to the surface as a set of labels, in a smart way that > e.g. takes the mode of the voxels that lie on the vector between equivalent > white and pial nodes (ie uses curvature and thickness information, tacitly > or explicitly)? > > the labels are not exactly on the ribbon. There are many voxels outside > the ribbon that are non zero. Like caudate etc. > > and some voxels that are within the ribbon but are zero because the > label data is was/is non-isotropic originally (which is the problem we want > to solve in fact). > > that would be great. > > Now let's say you already have labels on a mesh. > > can you generate a ribbon volume of labels, i.e. the opposite operation > to what I enquire about above (opposite but not inverse operation)? > > This is work in rhesus. So my pipeline is very barebones indeed, really > just > > mri_normalize > ... > mri_tesselate > mri_inflate/smooth/sphere > mris_fix_topology <-noaseg -noaprc> > mris_make_surfaces <-naseg -noaparc> > > I only have access to what is generated by that sequence or what I can > subsequently generate. > I can generate a freesurfer like ribbon with mris_fill. > > My understanding of labels and data mapping in general in freesurfer is > very poor. > > Maybe adapting one of your matlab scripts might be an idea, if there is > not another way? > > many thanks, > > Colin, > Sussex > > > _______________________________________________ > Freesurfer mailing listFreesurfer@nmr.mgh.harvard.eduhttps://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > > > >

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Monte Carlo simulation: Talairach coordinates
by Emily Boeke 25 Jun '13

25 Jun '13

Hi All, I'm running Monte Carlo simulations on functional data, and the coordinate information outputted in the cluster.summary file isn't making sense. Usually the coordinates for the clusters listed are Talairach coordinates, but in the .summary files I'm getting, the coordinates are labeled "VoxX VoxY VoxZ" instead of "TalX TalY TalZ" and the numbers are clearly not Talairach coordinates. Above the table, it says "Reporting Coordinates in Voxel Indices." I also noted that in the descriptive information above the table, it says "Registration: None: Tal Coords invalid." However, the .nii files I'm seeing look like I would expect them too. I'm using the same command line I've run before, so I have no idea why the .summary file looks different. Does anyone know why this would be? Thanks, Emily

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problem with surface area regression
by wen.zhang55 25 Jun '13

25 Jun '13

Dear Freesurfer, I have checked the mail list, none could answer my problem. I added up the value of all vertxes in the .area or .area.pial files, find that brain size did not contribute much to that vertex-sum. However, some experiment used total brain volume as a regreesion coefficient to remove brain size effect. In these case, with the comparison of surface area in vertex-to-vertex, is it proper to use the above vertex-sum as the regression coefficient to remove different brain size? Thank you very much! Cowen 2013-06-24 wen.zhang55

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freeview: create ROI in inflated surface
by Garikoitz Lerma-Usabiaga 25 Jun '13

25 Jun '13

Hi list, is it possible to create a ROI in an inflated surface within freeview or do I have to use tksurfer? It seems that I only can edit volume files. After exploratory mri_glmfit, I want to outline a ROI in fsaverage inflated surface and afterwards create a label to obtain CT averages per every subject. Many thanks! Gari

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fsaverage vertex index to talairach
by Cesar Echavarria 25 Jun '13

25 Jun '13

Hello, Anyone know of a fast way to get the talairach coordinates of a vertex index in fsaverage. A function or script is best since I want to do this for a large number of vertices. Thank you for any help you guys can provide. Cesar

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Fwd: DTI questions
by Rotem Saar 24 Jun '13

24 Jun '13

Hi there, Long time:). Well I wrote to the list several times regarding high FA values I got when performing DTI analysis. Today we know that the problem was an additional direction (we had 17 directions instead of 16 - we used a Philips scanner,1.5T). So we deleted the additional slices and the high values indeed disappeared, but then another problem came up (tried several subjects so the problem is not specific to a subject) - I noticed an artifact that I can't explain - please see the attached pictures. This artifact existed even before I deleted the additional slices, also - I see the artifact also when loading the masked volume...It is cyclic - run over all slices... any ideas ? I'm using version 5.2 and I know the command lines are correct (send it to u in the past). Thanks for your help Rotem

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Multiple inputs into recon-all -i
by ye tian 24 Jun '13

24 Jun '13

Dear David, I wonder whether there is a short cut for recon-all -s Barbara -i /path_to_data/scan1.dicom -i /path_to_data/scan2.dicom ... -i /path_to_data/scan100.dicom Recon-all -i takes only a single file as an input. A typical user, however, has hundreds of files for a particular subject. For example, the directory Barbara may have 100 scans. Therefore, the above command is necessary to include all the scans. I understand that I can write loops to a text file and then copy and paste to command line. However, I wonder whether there is a simpler way to input several files or even a directory to recon-all. Thank you very much! Sincerely, Ye

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HCP Releases Second Quarter of Brain Connectivity Data
by Jennifer Elam 24 Jun '13

24 Jun '13

June 13, 2013 (repost to Freesurfer list June 24, 2013) The Human Connectome Project (HCP) WU-Minn consortium is pleased to announce our second quarterly (Q2) release of HCP image and behavioral data. What’s in the HCP Q2 data release? The Q2 data include multimodal MRI and behavioral data collected from 68 healthy young adults scanned in winter 2012-2013. The current release expands the total (Q1+Q2) number of released healthy participant data for imaging and/or behavioral measures to 148, including 40 datasets that include the complete HCP protocol (T1w and T2w MRI, rfMRI, tfMRI, dMRI, and behavioral measures) and an additional 60 that include all modalities other than dMRI. The Q2 release also includes: · New preprocessing pipelines - Along with the newly processed Q2 datasets, the Q2 release also includes a complete regeneration of the minimally preprocessed data from Q1. We strongly encourage all investigators to update their existing Q1 data to stay current with HCP's latest and greatest. · More behavioral data, physiological data - Most of the collected behavioral/individual difference assessments and physiological data for functional MRI scans of Q1/Q2 participants is now available for a majority of subjects. · Restricted Data - Qualified investigators who are approved for restricted access will be given access to restricted data through the ConnectomeDB interface. · 40 dMRI datasets - Diffusion MRI data is being released for 40 unrelated Q1/Q2 subjects only because HCP has recently implemented an improved image reconstruction algorithm for dMRI data. Unprocessed and minimally preprocessed datasets based on these improved reconstructions for all Q1, Q2, and Q3 subjects will be included in the Q3 data release scheduled for August 2013. Access Q2 data on the HCP website. Explore, download, or order the entire HCP Q1+Q2 dataset (~3.5TB of data!) via the ConnectomeDB database ( http://humanconnectome.org/data/) Most HCP image and behavioral data is openly accessible to investigators worldwide who register and accept a limited set of Open Access Data Use Terms. Note: Please clear your browser cache before logging in to ConnectomeDB. Want more information? Check out the HCP Q2 Data Release Reference Manual ( http://humanconnectome.org/documentation/Q2/) for a comprehensive guide that includes details on imaging protocols, behavioral measures, and information that will help users obtain and analyze the Q2 data. Detailed descriptions of many HCP methods are available in eight papers now in press for a special issue of NeuroImage in 2013 (Van Essen et al., 2013, Ugurbil et al., 2013, Glasser et al., 2013, Smith et al., 2013, Barch et al., 2013, Sotiropolous et al., 2013, Marcus et al., 2013, and Larson-Prior et al., 2013). For those who choose to download the HCP data and begin to analyze it, we encourage you to join and be active in the hcp-users discussion group ( http://www.humanconnectome.org/contact/#subscribe) so that you can tune in to technical discussions on issues that may be of interest. Please send us your questions and comments anytime to info(a)humanconnectome.org. Best, The WU-Minn HCP Consortium Jennifer Elam, Ph.D. Outreach Coordinator, Human Connectome Project Washington University School of Medicine Department of Anatomy and Neurobiology, Box 8108 660 South Euclid Avenue St. Louis, MO 63110 314-362-9387 elamj(a)pcg.wustl.edu www.humanconnectome.org

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Using the T2 pial flag for pial refinement
by Michael Kranz 24 Jun '13

24 Jun '13

Hi all, I'm having trouble determining whether or not to use our T2 images for the new pial refinement feature. *Most importantly, I'm wondering if our T2 image parameters are sufficient for the T2 pial refinement. The parameters of our T2 images are as follows:* T2 TSE overlay with a voxel size of 1.1x1.1x3.5 mm (slice thickness). A couple other studies in our lab have a voxel size of 0.9x0.9x4.0 mm. Note that our MPRAGE voxel size is .9x.9x.9mm. In your release notes, it states we should uaround a 1x1x1mm (let me know if you need additional specifications such as geometry bandwidth etc): "T2/FLAIR used for pial surface refinement: if you have T2 or FLAIR scans ~1mm^3, then they can be used by the recon-all stream to refine the pial surfaces". I have experienced about 1/4 of our subjects with errors using the T2 pial flag. As a next step, if you think the parameters are acceptable, then I can send you some screen shots different errors that I have encountered wit these subjects. Best, Mike

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