AFNI program: 3dclust

Program: 3dclust 
Author:  RW Cox et al 
Date:    29 Nov 2001 

Simple-minded Cluster Detection in 3D Datasets
Usage: 3dclust [editing options] [other options] rmm vmul dset ...
  where rmm  = cluster connection radius (mm);
        vmul = minimum cluster volume (micro-liters)
              * If rmm = 0, then clusters are defined
                 by nearest-neighbor connectivity.
              * If vmul = 0, then all clusters are kept.
              * If vmul < 0, then abs(vmul) is the minimum
                 number of voxels allowed in a cluster.
        dset = input dataset (more than one allowed).
  The report is sent to stdout.

Options
-------
* Editing options are as in 3dmerge
  (including -1thresh, -1dindex, -1tindex, -dxyz=1 options)

* -noabs      => Use the signed voxel intensities (not the abs
                  value) for calculation of the mean and SEM

* -summarize  => Write out only the total nonzero voxel
                  count and volume for each dataset

* -nosum      => Suppress printout of the totals

* -verb       => Print out a progress report (to stderr)
                  as the computations proceed

* -quiet      => Suppress all non-essential output

* -mni        => If the input dataset is in +tlrc coordinates, this
                  option will stretch the output xyz-coordinates to the
                  MNI template brain.
           N.B.: The MNI template brain is about 5 mm higher (in S),
                  10 mm lower (in I), 5 mm longer (in PA), and tilted
                  about 3 degrees backwards, relative to the Talairach-
                  Tournoux Atlas brain.  For more details, see
                    http://www.mrc-cbu.cam.ac.uk/Imaging/mnispace.html
           N.B.: If the input dataset is not in +tlrc coordinates,
                  then the only effect is to flip the output
                  coordinates to the 'LPI' (neuroscience) orientation.
                  (As if you gave the '-orient LPI' option.)

* -isovalue   => Clusters will be formed only from contiguous (in the
                  rmm sense) voxels that also have the same value.
           N.B.: The normal method is to cluster all contiguous
                  nonzero voxels together.

* -isomerge   => Clusters will be formed from each distinct value
                  in the dataset; spatial contiguity will not be
                  used (but you still have to supply rmm and vmul
                  on the command line).
           N.B.: 'Clusters' formed this way may well have components
                  that are widely separated!

* -prefix ppp => Write a new dataset that is a copy of the
                  input, but with all voxels not in a cluster
                  set to zero; the new dataset's prefix is 'ppp'
           N.B.: Use of the -prefix option only affects the
                  first input dataset

Nota Bene
---------
* The program does not work on complex- or rgb-valued datasets!
* Using the -1noneg option is strongly recommended!
 * 3D+time datasets are allowed, but only if you use the
   -1tindex and -1dindex options.
* Bucket datasets are allowed, but you will almost certainly
   want to use the -1tindex and -1dindex options with these.
* SEM values are not realistic for interpolated data sets! 
   A ROUGH correction is to multiply the SEM of the interpolated
   data set by the square root of the number of interpolated 
   voxels per original voxel. 
* If you use -dxyz=1, then rmm should be given in terms of
   voxel edges (not mm) and vmul should be given in terms of
   voxel counts (not microliters).  Thus, to connect to only
   3D nearest neighbors and keep clusters of 10 voxels or more,
   use something like '3dclust -dxyz=1 1.01 10 dset+orig'.
   In the report, 'Volume' will be voxel count, but the rest of
   the coordinate dependent information will be in actual xyz
   millimeters.
* The default coordinate output order is DICOM.  If you prefer
    the SPM coordinate order, use the option '-orient LPI' or
    set the environment variable AFNI_ORIENT to 'LPI'.  For more
    information, see file README.environment.