Ziad is the likely suspect for answering this question.

To begin
our goal: a database of spatially normalized cortical thickness datasets for comparison to abnormal datasets.
we have: ~220 high res SPGR brain images from our 1.5T GE signa collected over the past 10 years

We began, and have invested quite a bit of time in using BrainSuite, as this is what our neuroradiologist used.
Initially I was not thinking about downstream use in SUMA etc.

So from my readings it appears that BrainSuite and FreeSurfer are similar in that they both produce cortical thickness measurements.
SUMA can read FSL files. It does not appear to have a DFS import fuction, but from here:

[users.loni.ucla.edu]

and here

[afni.nimh.nih.gov]

It appears that import could happen.

But I am not sure that's what I need to do. I need them spatially normalized.

BrainSuite references a normal image, but does not appear to be spatially normalizing to that standard space.

The LONI BrainSuite support forum seem to be somewhat quiescent at present, albeit I haven't asked about spatial normalization.

So I am not sure whether I just need to start over completely in FSL, or whether there is a way to obtain spatially normalized surface meshes from our existing pial surfaces with the extant cortical thickness data on them.

And here's another problem: one that I did post in BrainSuite's forum and am awaiting a response to:
FSL and BrainSuite appear to be providing different cortical thickness values.
This is based on two things:
The first is the color scale used by BrainSuite. See this post on their forum:
[forum.loni.ucla.edu]
It seems that most of our brains have most regions with 4-5mm thickness, which is quite different from the nice histogram in Fischl and Dale's PNAS article referenced also in the above post. The histogram data is also consistent with cortical thickness data in general - histopathology, etc.
This could be a miniscule problem related to BrainSuite scaling however.

I'm rambling. Sorry.

Questions:
1. Should I start over with FSL?
2. If not, what's the best pathway for obtaining spatially normalized cortical thickness data from our extant DFS data?

Cheers,
JP