Dear FSL users,
I get FAST segmentation problems. When I specify:
fast -g -b -B -o output_image -p input_image (input_image=a standardised to
MNI, brain only, T1.nii.gz), I get the message:
Exception: Not enough classes detected to init KMeans.
Following from this, when I specify:
[P1] fast -g -a (matrix from FLIRT) -b -B -o output_image -v -p input_image
(using prior to initialise parameter estimation) OR
[P2] fast -g -a (matrix from FLIRT) -b -B -o output_image -P -v -p
input_image (using priors throughout)
I get the problematic images I have attached. I have checked the input
images and they are fine (previous steps: (a)ANALYZE T1(original) ->
(b)NIFTI-> (c)fslswapsim-> (d) bet-> (e)FLIRT). I get the same exception
message even when, regarding the input image, I omit steps (c), or even
steps (b) AND (c).
HOWEVER, command  works fine (and [P1] has done so previously) when the
input image has not been through FLIRT (i.e. step (e) was omitted, and the
input image to FAST is not registered to MNI).
Any ideas of what I may be doing wrong?
Thanks so much for your help!