I have 10 brainstem ROI masks(.nii format in MNI space), and 16 subcortical regions resulting from freesurfer.
I have previously acquired the structural matrix file of HCP atlas, now I want to conduct the structural connectivity among these ROI regions, is there an easy way that tck2connectome to do it?
For my understanding, I have to firstly transform the .nii masks to each subject, know I’m struggling with the next steps: do I need to combine all ROIs into one .mif file?
Here’s something that might work if you just wanted to probe connectivity between the 10 brainstem and 16 subcortical ROIs (which have the same resolution)…
I think you will need a single mif file (let’s call it the parcellation image) containing all 26 regions, indexed from 1-26. This will result in a connectome matrix that has a size of 26x26 after using tck2connectome.
One way of generating this parcellation image is to extract each ROI as a separate binary mask (see mrcalc with -eq option), and reindex the binary mask with a unique value from 1 to 26 (using something like mrcalc <binary_mask> <index> -mult <re-indexed_mask.mif>).
Then add all the re-indexed masks together to get a parcellation image. This image should only contain values from 1-26.
It would be a good idea to ensure that the ROIs are indeed non-overlapping prior to adding (overlapping ROIs that sum together will result in mislabelled voxels at the boundary of overlapping masks…).