Dear All,
I stumbled upon the following passage in the segmentation help text:
'A more accurate estimate of a bias field can be obtained by including
prior knowledge about the distribution of the fields likely to be
encountered by the correction algorithm.'
I wonder if this only refers to the amount of inhomogeneity (likely a
ballpark number) or it is it possible to, for example, use another
algorithms output as a more informed starting estimate. Alternatively,
one could take the bias field from a first iteration and feed that into
a second pass segmentation run. I realize this would take more time but
for very inhomogeneous data (surface coils, high-field etc.) it may
result in an improvement of tissue labeling.
So bottomline, my question is: Has anyone experimented with providing 3D
inhomogeneity estimates as starting parameters for the spm5 segmentation
algorithm?
Best,
Marko
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Marko Wilke (Dr.med./M.D.)
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Universitäts-Kinderklinik University Children's Hospital
Abt. III (Neuropädiatrie) Dept. III (Pediatric neurology)
Hoppe-Seyler-Str. 1, D - 72076 Tübingen
Tel.: (+49) 07071 29-83416 Fax: (+49) 07071 29-5473
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