Usage: 3dAutomask [options] dataset
Input dataset is EPI 3D+time, or a skull-stripped anatomical.
Output dataset is a brain-only mask dataset.

This program by itself does NOT do 'skull-stripping'.  Use
program 3dSkullStrip for that purpose!

 + 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,
   which will be 1 inside the mask and 0 outside the mask.

  -prefix ppp = Write mask into dataset with prefix 'ppp'.
                 [Default == 'automask']

  -apply_prefix ppp = Apply mask to input dataset and save
                masked dataset. If an apply_prefix is given
                and not the usual prefix, the only output
                will be the applied dataset

  -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 (erode) the mask 'pp' times,
                  then unpeel (dilate). Using NN2 neighborhoods,
                 clips off protuberances less than 2*pp voxels
                 thick. Turn off by setting to 0. [Default == 1]

  -NN1 -NN2 -NN3 = Erode and dilate using different neighbor definitions
                 NN1=faces, NN2=edges, NN3= corners [Default=NN2]
                 Applies to erode and dilate options, if present.
                 Note the default peeling processes still use NN2
                 unless the peels are set to 0

  -nbhrs nn   = Define the number of neighbors needed for a voxel
                 NOT to be eroded.  The 18 nearest neighbors in
                 the 3D lattice are used, so 'nn' should be between
                 6 and 26. [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).

  -depth DEP  = Produce a dataset (DEP) that shows how many peel
                operations it takes to get to a voxel in the mask.
                The higher the number, the deeper a voxel is located
                in the mask. Note this uses the NN1,2,3 neighborhoods
                above with a default of 2 for edge-sharing neighbors
          None of -peels, -dilate, or -erode affect this option.
How to make an edge-of-brain mask from an anatomical volume:
* 3dSkullStrip to create a brain-only dataset; say, Astrip+orig
* 3dAutomask -prefix Amask Astrip+orig
* Create a mask of edge-only voxels via
   3dcalc -a Amask+orig -b a+i -c a-i -d a+j -e a-j -f a+k -g a-k \
          -expr 'ispositive(a)*amongst(0,b,c,d,e,f,g)' -prefix Aedge
  which will be 1 at all voxels in the brain mask that have a
  nearest neighbor that is NOT in the brain mask.
* cf. '3dcalc -help' DIFFERENTIAL SUBSCRIPTS for information
  on the 'a+i' et cetera inputs used above.
* In regions where the brain mask is 'stair-stepping', then the
  voxels buried inside the corner of the steps probably won't
  show up in this edge mask:
  Only the 'a' voxels are in this edge mask, and the 'b' voxels
  down in the corners won't show up, because they only touch a
  0 voxel on a corner, not face-on.  Depending on your use for
  the edge mask, this effect may or may not be a problem.

++ Compile date = Jan 17 2020 {AFNI_20.0.00:linux_ubuntu_16_64}