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Sorry, missed this one before I got the personal invitation to respond.
I believe this would use a FreeSurfer registration of the group parcellation to the individual. That is a folding-based registration and one can do slightly better than that with MSMSulc. One can do much better than that with MSMAll,
which is an areal-feature-based registration. Finally, a direct areal classifier can do even better, and we are working on a new version of that that is more shareable. Also, there will likely be improvements to the various registration methods in the future.
Coalson et al., (2018) PNAS has some comparisons of different approaches currently available.
Matt.
From: <freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of "Boa Sorte Silva, Narlon" <narlon.silva@ubc.ca>
Reply-To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
Date: Monday, November 27, 2023 at 4:20 PM
To: freesurfer <freesurfer@nmr.mgh.harvard.edu>
Subject: [Freesurfer] FreeSurfer Parcellation Using Glasser's Atlas (HCP-MMP1)
Hi there,
I am hoping to extract cortical thickness and volume data from FreeSurfer-processed subjects using the
HCP-MMP1 atlas (Glasser et al 2016 Nature). I have found many discussions in the email list but I wasn’t able to understand whether this procedure can be reliably done using .annot files.
I have found ?h.HCPMMP1.annot files online (e.g., ggsegGlasser: MailScanner
has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be https://github.com/ggseg/ggsegGlasser/tree/master/data-raw) in fsaverage space, which I have resampled to the subject’s space using
mri_surf2surf as follows:
# Apply Glasser’s 2016 HCP-MMIP1.0 atlas
mri_surf2surf \
--hemi ${hemi} \
--srcsubject fsaverage \
--trgsubject ${id} \
--sval-annot fsaverage/label/${hemi}.HCPMMP1.annot \
--tval ${SUBJECTS_DIR}/${id}/label/${hemi}.HCPMMP1.annot
Then I extracted the stats using this command:
# Extract Thickness and Volume stats
mris_anatomical_stats \
-a ${SUBJECTS_DIR}/${id}/label/${hemi}.HCPMMP1.annot \
-f ${SUBJECTS_DIR}/${id}/stats/${hemi}.HCPMMP1.stats \
-b ${id} ${hemi}
My question is whether the output from this procedure can be reliably used as an accurate version of the HCP-MMP1 parcellated regions in the subject’s native space OR whether a more involved process is needed to
generate the parcellation.
Thank you for your help
Best regards,
Nárlon Cássio
Nárlon C Boa Sorte Silva PhD (He, Him, His)
CIHR and MSHR BC/CLEAR Postdoctoral Research Fellow
Aging, Mobility, and Cognitive Health Lab
Djavad Mowafaghian Centre for Brain Health
Department of Physical Therapy, Faculty of Medicine
University of British Columbia
Vancouver, Canada
Twitter: @BoaNarlon
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