Re: [HCP-Users] Custom parcellation for HCP data

[Harms, Michael]

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 _______________________________________________ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users   The materials in this message are private and may contain Protected Healthcare Information or other information of a sensitive nature. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this email in error, please immediately notify the sender via telephone or return mail. _______________________________________________ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users