Hi Jenn,

Thanks for your advice about the structural extended preprocessed data
packages. Precisely what we needed. Is this data available as part of
Connectome in a Box? i.e., Can we request this data to be included when we
order a copy of the 900 subjects release?

Thank you,

Simon


On 16 November 2015 at 11:09, Jennifer Elam <[email protected]> wrote:

> Hi Simon,
>
> The HCP Structural Extended Preprocessed packages for each subject
> (available from the Download packages page with the Processing level filter
> set to Preprocessed) includes the FreeSurfer v5.3.0-HCP output directory
> created by the HCP Structural pipeline. These are intermediate files that
> are not in NIFTI/GIFTI/CIFTI format.
>
>
>
> Best,
>
> Jenn
>
>
>
> 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
> [email protected]
> www.humanconnectome.org
>
>
>
> *From:* [email protected] [mailto:
> [email protected]] *On Behalf Of *Simon Baker
> *Sent:* Sunday, November 15, 2015 5:41 PM
> *To:* [email protected]
>
> *Subject:* Re: [HCP-Users] Custom parcellation for HCP data
>
>
>
> Thanks for your email Matt.
>
>
>
> Do you happen to know the names of those packages?
>
>
>
> Given that our custom parcellation is in the form of an annotation file
> (rather than a gifti file), can you suggest a way to get our custom
> parcellation from an atlas surface to a subject's volume using Connectome
> Workbench?
>
>
>
> Alternatively, is there a way to generate a custom parcellation using
> Connectome Workbench?
>
>
>
> Simon
>
>
>
>
>
> On 12 November 2015 at 03:33, Glasser, Matthew <[email protected]> wrote:
>
> I think this might be way more complicated than is needed.  I believe
> there are structural extended packages that would allow you to run a
> FreeSurfer command without needing to replicate FreeSurfer files.  As for
> how to get a parcellation from an atlas surface to a subject’s volume, I
> could tell you how to do that using Connectome Workbench tools, file
> formats, and our atlas, but I don’t know the details for FreeSurfer.
>
>
>
> Peace,
>
>
>
> Matt.
>
>
>
> *From: *Simon Baker <[email protected]>
> *Date: *Tuesday, November 10, 2015 at 11:34 PM
> *To: *"[email protected]" <[email protected]>
> *Cc: *"Harms, Michael" <[email protected]>, Timothy Coalson <[email protected]>,
> Matt Glasser <[email protected]>
>
>
> *Subject: *Re: [HCP-Users] Custom parcellation for HCP data
>
>
>
> Thanks for the pointers Michael, Tim, and Matt. We've tried a range of
> approaches but we're still having trouble creating the custom parcellation.
> Below describes the updated version of our pipeline. Although this version
> improves the spatial alignment between the custom parcellation and the T1w
> volume, the quality of the parcellation is still lacking compared to e.g.
> ribbon.nii.gz.
>
>
>
> --
>
>
>
> 1. Create a high-resolution annotation (parcellation) by randomly
> parcellating the fsaverage surface into N regions of approximately equal
> volume.
>
>
>
> 2. Map the annotation from the source subject (fsaverage) to the target
> subject using mri_surf2surf.
>
>
>
> mri_surf2surf --srcsubject fsaverage --hemi xh --sval-annot highres.annot
> --trgsubject ${SUBJECTID} --srcsurfreg sphere.reg --trgsurfreg
> /MNINonLinear/Native/${SUBJECTID}.X.sphere.native.surf.gii --tval
> xh.highres.annot
>
>
>
> 3. Obtain vertices and faces data from
> /MNINonLinear/Native/${SUBJECTID}.X.white.native.surf.gii
>
>
>
> 4. Using the vertices and faces data obtained in step 3 as inputs for the
> write_surf Matlab function, create the xh.white surface file.
>
>
>
> 5. Obtain thickness data from
> /MNINonLinear/Native/${SUBJECTID}.X.thickness.native.shape.gii
>
>
>
> 6. Using T1wImage = /T1w/T1w_acpc_dc_restore.nii.gz and T1wImageBrain =
> /T1w/T1w_acpc_dc_restore_brain.nii.gz, we replicate some of the steps found
> in HCP's FreeSurferPipeline.sh in order to generate /mri/orig.mgz.
> Specifically:
>
>
>
> #Make Spline Interpolated Downsample to 1mm
>
> Mean=`fslstats T1wImageBrain -M`
>
>
>
> flirt -interp spline -in T1wImage -ref T1wImage -applyisoxfm 1 -out
> T1wImage_1mm
>
>
>
> applywarp --rel --interp=spline -i T1wImage -r T1wImage_1mm
> --premat=/usr/local/fsl/etc/flirtsch/ident.mat -o T1wImage_1mm
>
>
>
> applywarp --rel --interp=nn -i T1wImageBrain -r T1wImage_1mm
> --premat=/usr/local/fsl/etc/flirtsch/ident.mat -o T1wImageBrain_1mm
>
>
>
> fslmaths T1wImage_1mm -div $Mean -mul 150 -abs T1wImage_1mm
>
>
>
> mri_convert T1wImage_1mm /mri/orig/001.mgz
>
>
>
> #Initial Recon-all Steps
>
> recon-all -subjid ${SUBJECTID} -sd ${SUBJECTS_DIR} -motioncor -talairach
> -nuintensitycor -normalization
>
>
>
> 7. Convert the custom parcellation annotation into a custom parcellation
> volume using mri_label2vol, with /mri/orig.mgz serving as the output
> template volume.
>
>
>
> mri_label2vol --annot xh.custom.annot --temp /mri/orig.mgz --identity
> --proj frac 0 1 .1 --subject ${SUBJECTID} --hemi xh --o xh_custom_vol.mgz
>
>
>
> 8. Resample and reslice the custom parcellation volume.
>
>
>
> mri_convert --resample_type nearest --reslice_like T1wImage
> xh_custom_vol.mgz xh_custom_vol.nii
>
>
>
> 9. Combine the resampled and resliced custom parcellation volume from each
> hemisphere to create a single custom parcellation volume (custom_vol.nii).
>
>
>
> 10. Find c_ras offset and generate matrix
>
>
>
> MatrixX=$(mri_info --cras T1wImage | cut -d " " -f 1)
>
> MatrixY=$(mri_info --cras T1wImage | cut -d " " -f 2)
>
> MatrixZ=$(mri_info --cras T1wImage | cut -d " " -f 3)
>
> echo "1 0 0 ""$MatrixX" > c_ras_xfm.mat
>
> echo "0 1 0 ""$MatrixY" >> c_ras_xfm.mat
>
> echo "0 0 1 ""$MatrixZ" >> c_ras_xfm.mat
>
> echo "0 0 0 1" >> c_ras_xfm.mat
>
>
>
> 11. Invert the c_ras offset matrix
>
>
>
> convert_xfm -omat c_ras_xfm_inv.mat -inverse c_ras_xfm.mat
>
>
>
> 12. Apply the inverted c_ras offset matrix to the custom parcellation
> volume (custom_vol.nii)
>
>
>
> flirt -in custom_vol.nii -applyxfm -init c_ras_xfm_inv.mat -out
> parcellation.nii -paddingsize 0.0 -interp nearestneighbour -ref T1wImage
>
>
>
> 13. [Not sure why, but then we had to] Warp the output from the previous
> step in order to align the parcellation with T1wImage (i.e.,
> /T1w/T1w_acpc_dc_restore.nii.gz).
>
>
>
> applywarp --rel --interp=nn -i parcellation.nii -r T1wImage -w
> /MNINonLinear/xfms/standard2acpc_dc.nii.gz -o parcellation_native.nii
>
>
>
> 14. See attached screenshot2.jpeg showing /T1w/T1w_acpc_dc_restore,
> /T1w/ribbon (blue), and parcellation_native (yellow).
>
>
>
> --
>
>
>
> The alignment of parcellation_native is a bit off and it appears to be
> grainy/pixelated. Do you have any suggestions as to why this is the case?
>
>
>
> Kind regards,
>
>
>
> Simon Baker
>
> Brain & Mental Health Laboratory
>
> Institute of Cognitive & Clinical Neuroscience
>
> Monash University
>
>
>
>
>
> On 20 October 2015 at 09:20, Glasser, Matthew <[email protected]> wrote:
>
> FreeSurfer might do it if you simply specify the correct extension, but if
> not, mris_convert will do the conversion.
>
>
>
> Peace,
>
>
>
> Matt.
>
>
>
> *From: *<[email protected]> on behalf of Timothy
> Coalson <[email protected]>
> *Date: *Monday, October 19, 2015 at 4:44 PM
> *To: *"Harms, Michael" <[email protected]>
> *Cc: *"[email protected]" <[email protected]>,
> Simon Baker <[email protected]>
> *Subject: *Re: [HCP-Users] Custom parcellation for HCP data
>
>
>
> Additionally, if you generate a cortex-only parcellation, you shouldn't
> need to put it into a volume to use it with the HCP CIFTI data.  However,
> I'm not sure how to get freesurfer to write GIFTI label files, and unless
> you generate it on the fs_LR 32k mesh, you'll need to resample it (via
> registered sphere surfaces).  If you can get the label data into matlab,
> though, you can write it as .func.gii files, and use wb_command to turn it
> into label.gii, and then to .dlabel.nii for use with CIFTI data.  Some care
> may be needed to keep the right and left labels separate.
>
>
>
> Tim
>
>
>
>
>
> On Mon, Oct 19, 2015 at 10:08 AM, Harms, Michael <[email protected]> wrote:
>
>
>
> Hi,
>
> Did you see this recent thread on the list:
>
> http://www.mail-archive.com/hcp-users%40humanconnectome.org/msg01910.html
>
>
>
> cheers,
>
> -MH
>
>
>
> --
>
> Michael Harms, Ph.D.
>
> -----------------------------------------------------------
>
> Conte Center for the Neuroscience of Mental Disorders
>
> Washington University School of Medicine
>
> Department of Psychiatry, Box 8134
>
> 660 South Euclid Ave. Tel: 314-747-6173
>
> St. Louis, MO  63110 Email: [email protected]
>
>
>
> *From: *Simon Baker <[email protected]>
> *Date: *Sunday, October 18, 2015 8:16 PM
> *To: *"[email protected]" <[email protected]>
> *Subject: *[HCP-Users] Custom parcellation for HCP data
>
>
>
> Hi all,
>
>
>
> We want to create a custom parcellation for use with the connectome
> project data. However, we have not been able to achieve accurate spatial
> alignment between the random parcellation volume and the T1w volume.
> Specifically, there appears to be an "offset," possibly due to a mismatch
> between the origin of these volumes. In the following we describe the
> relevant steps of our pipeline. Please suggest any changes that might help
> to resolve the issue.
>
>
>
> 1. Create a high-resolution annotation (parcellation) by randomly
> parcellating the fsaverage surface into N regions of approximately equal
> volume.
>
>
>
> 2. Map the annotation from the source subject (fsaverage) to the target
> subject using mri_surf2surf.
>
>
>
> mri_surf2surf --srcsubject fsaverage --hemi lh --sval-annot highres.annot
> --trgsubject ${SUBJECTID} --srcsurfreg sphere.reg --trgsurfreg
> ${SUBJECTS_DIR}/${SUBJECTID}/MNINonLinear/Native/${SUBJECTID}.L.sphere.native.surf.gii
> --tval lh.highres.annot
>
>
>
> [repeat for rh]
>
>
>
> 3. Obtain vertices and faces data from
> ${SUBJECTS_DIR}/${SUBJECTID}/MNINonLinear/Native/${SUBJECTID}.L.white.native.surf.gii
>
>
>
> [repeat for rh]
>
>
>
> 4. Using the vertices and faces data obtained in step 3 as inputs for the
> write_surf Matlab function, create the lh.white surface file.
>
>
>
> [repeat for rh]
>
>
>
> 5. Obtain thickness data from
> ${SUBJECTS_DIR}/${SUBJECTID}/MNINonLinear/Native/${SUBJECTID}.L.thickness.native.shape.gii
>
>
>
> [repeat for rh]
>
>
>
> 6. Convert the annotation into a volume using mri_label2vol.
>
>
>
> mri_label2vol --annot lh.highres.annot --temp
> ${SUBJECTS_DIR}/${SUBJECTID}/T1w/T1w_acpc_dc_restore.nii.gz --identity
> --proj frac 0 1 .1 --subject ${SUBJECTID} --hemi lh --o vol_lh.nii
>
>
>
> [repeat for rh]
>
>
>
> 7. Configure the volume (remove unwanted ROIs).
>
>
>
> [repeat for rh]
>
>
>
> 8. Combine the configured volumes from each hemisphere to create the
> random parcellation volume.
>
>
>
> 9. Overlay the random parcellation volume on the template volume.
>
>
>
> See attached screenshot.jpeg showing the misalignment between the random
> parcellation volume and the template volume.
>
>
>
> Kind regards,
>
>
>
> Simon Baker
>
> Brain & Mental Health Laboratory
>
> Institute of Cognitive & Clinical Neuroscience
>
> Monash University
>
>
>
> _______________________________________________
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> [email protected]
> http://lists.humanconnectome.org/mailman/listinfo/hcp-users
>
>
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