Main bet2 options: -f f fractional intensity threshold (0-1); default=0.5; smaller values give larger brain outline estimates -g g vertical gradient in fractional intensity threshold (-1-1); default=0; positive values give larger brain outline at bottom, smaller at top Variations on default bet2 functionality (mutually exclusive options): -R This option runs more robust brain centre estimation; it repeatedly calls bet2, each time using the same input image and the same main options, except that the -c option (which sets the starting centre of the brain estimation) is set each time to the centre-of-gravity of the previously estimated brain extraction. The primary purpose is to improve the brain extraction when the input data contains a lot of non-brain matter - most likely when there is a lot of neck included in the input image. By iterating in this way the centre-of-gravity should move up each time towards the true centre, resulting in a better final estimate. The iterations stop when the centre-of-gravity stops moving, up to maximum of 10 iterations. -S This attempts to cleanup residual eye and optic nerve voxels which bet2 can sometimes leave behind. This can be useful when running SIENA or SIENAX, for example. Various stages involving standard-space masking, morphpological operations and thresholdings are combined to produce a result which can often give better results than just running bet2. -B This attempts to reduce image bias, and residual neck voxels. This can be useful when running SIENA or SIENAX, for example. Various stages involving FAST segmentation-based bias field removal and standard-space masking are combined to produce a result which can often give better results than just running bet2. From: http://web.mit.edu/fsl_v5.0.8/fsl/doc/wiki/BET(2f)UserGuide.html
标签: BET
