Hi Geoffrey,
I saw your post below and was interested in knowing a bit more about the
approach you used. Would you mind explaining how you did it a bit in more
detail?
Which smoothed image were you referring to? And the T1 was the T1 in
'templates'?
Did you use the result of registration as the input for opts.regtype in
spm_preproc?
Many thanks,
Lucia
Hi Herve,
Just to add to this, although I'm sure John will reply to this
eventually. I think part of the problem is that the prior for
'non-brain tissue' does not model non-brain tissue ie skull, blood
vessels, fat, air... very well and the original affine registration can
be poor because it registers the brain to the prior probability maps.
John's working on something that models these classes more explicitly.
I've personally worked around it by doing an initial affine registration
of the smoothed image to the MNI T1 atlas, and using that as an input to
spm_preproc for the affine.
Geoffrey
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