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 <mha...@wustl.edu> 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: mha...@wustl.edu
>
> From: Simon Baker <simonteba...@gmail.com>
> Date: Sunday, October 18, 2015 8:16 PM
> To: "hcp-users@humanconnectome.org" <hcp-users@humanconnectome.org>
> 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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>
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