Dear Freesurfers,
From the Wiki Freesurfer surface stream follows something like:
1. Affine registration to Tal. 2. Bias correction and skull stripping 3. Classify WM 4. Cut hemisphere planes 5. Tile WM surface 6. Refine WM surface following GM-WM intensity gradients 7. Nudge (nudge?) WM surface to follow the GM-CSF gradient to generate pial surface 8. Labeling Data Set 9. Stats
May I ask which couple of these steps tend to be the most computationally taxing/longest to complete?
Also, I'm not sure I understand #7. Is the WM surface scaled in some sense to approximate the GM-CSF boundary, or is this just a refinement step like #6 of a surface that already approximates the GM-CSF boundary?
Thanks, I've spent most of my time working with the sub-cortical stream. - Joshua