AFNI program: 3dAutomask

Usage: 3dAutomask [options] dataset
Input dataset is EPI 3D+time.
Output dataset is a brain-only mask dataset.
Method:
 + Uses 3dClipLevel algorithm to find clipping level.
 + Keeps only the largest connected component of the
   supra-threshold voxels, after an erosion/dilation step.
 + Writes result as a 'fim' type of functional dataset.
Options:
  -prefix ppp = Write mask into dataset with prefix 'ppp'.
                 [Default == 'automask']
  -clfrac cc  = Set the 'clip level fraction' to 'cc', which
                 must be a number between 0.1 and 0.9.
                 A small 'cc' means to make the initial threshold
                 for clipping (a la 3dClipLevel) smaller, which
                 will tend to make the mask larger.  [default=0.5]
  -nograd     = The program uses a 'gradual' clip level by default.
                 To use a fixed clip level, use '-nograd'.
                 [Change to gradual clip level made 24 Oct 2006.]
  -peels pp   = Peel the mask 'pp' times, then unpeel.  Designed
                 to clip off protuberances less than 2*pp voxels
                 thick. [Default == 1]
  -nbhrs nn   = Define the number of neighbors needed for a voxel
                 NOT to be peeled.  The 18 nearest neighbors in
                 the 3D lattice are used, so 'nn' should be between
                 9 and 18.  [Default == 17]
  -q          = Don't write progress messages (i.e., be quiet).
  -eclip      = After creating the mask, remove exterior
                 voxels below the clip threshold.
  -dilate nd  = Dilate the mask outwards 'nd' times.
  -erode ne   = Erode the mask inwards 'ne' times.
  -SI hh      = After creating the mask, find the most superior
                 voxel, then zero out everything more than 'hh'
                 millimeters inferior to that.  hh=130 seems to
                 be decent (i.e., for Homo Sapiens brains).

++ Compile date = Jul 24 2008