Create subject level surface parcellations. Default output is in MNI space, modifcation for other spaces (eg native) is possible.
Curent capabilities are the "augmented Schaefer" (Schaefer cortical + Tian subcortical) at three scales (116, 232, and 454 parcels). See: https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Schaefer2018_LocalGlobal and: https://github.com/yetianmed/subcortex/tree/master/Group-Parcellation/3T/Subcortex-Only
As well as 5 scales of Lausanne. (Thanks Andrea Luppi of for providing the fsaverage labels for these.)
Requirements: python fsl workbench freesurfer
Steps:
- obtain warp files if you do not already have using get_anat2std_warps.sh subject_ID
This script may be modified to suit your particular situation. As currently written it will take a T1.mgz from freesurfer outputs and create warp files however the amount of computation time needed could be reduced if you already have 1 warp file, and only need to create the inverse (near the end of the script), OR if you have T1 in a orientation and space closer to MNI - you can use fnirt directly rather than fsl_anat.
- Once you have anat2mni and mni2anat warp files, create_subject_atlases.sh subject_ID atlas
available inputs for atlas (second arg) are: sch116 sch232 sch454 ls83 ls129 ls234 ls463 ls1015 (only handles one at a time)
Will need to set dirs at the begining of each script.
Kudos to Keith Jamison of the CoCo Lab for much of the heavy lifting.