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