Hi MRtrix3 Experts,
I’m trying to convert FD, FC and FDC from an FBA analysis into voxel-wise maps so that they can eventually be compared with other voxel-based diffusion measures.
I found the previous discussions on fixel2voxel, and my understanding is that voxel-wise FD can be obtained by summing the FD of multiple fixels within a voxel.
For a test subject, I tried:
fixel2voxel fd.mif sum FD_voxel.mif
This gives me FD in the population-template voxel space.
What I’m mainly unsure about is what should be done after this if I want the final maps in the same standard/MNI space as my other diffusion measures.
Would it be appropriate to:
template fixels
→ fixel2voxel
→ template voxel map
→ warp back to subject space
→ resample to the subject’s native DWI/FA grid
→ apply the existing FA-derived TBSS transformation
Or, since the FBA measures are already in the population-template space, would it be better to register the population template to MNI and transform the voxelized maps directly to MNI space?
I also wanted to clarify two related points:
For FC, is an FD-weighted mean of log(FC) the recommended way to obtain one value per voxel?
For FDC, what is the recommended fixel-to-voxel operation when there are multiple fixels within a voxel?
And finally, is it reasonable to apply TBSS skeleton projection to voxelized FD/FC/FDC, or would that change the interpretation of these FBA-derived measures in a way that makes this approach inappropriate?
I wanted to confirm the correct approach before proceeding further.
Thanks!