The difference is that bet works on a single 3D image and
betfunc applies a bet mask (taken from the first time point) to a
whole 4D data set. Note that betfunc also enlarges (dilates)
the mask slightly to allow for some inaccuracies in the placement
of subsequent images with respect to the first time point.
So if you want to mask out noisy non-brain stuff in a functional
(4D) series, then use betfunc.
All the best,
On Thursday, January 22, 2004, at 04:03 pm, Wei Qiu wrote:
There are bet and betfunc in FSL. What's different? Thanks!
I have a functional data set which is the T2* map. There are lots noise
outside of the brain yet I would like to use this inside brain data. Is
any quick way I can mask the brain? Thank you in advance!