Usage: 3dDTtoDWI [options] gradient-file I0-dataset DT-dataset

Computes multiple gradient images from 6 principle direction tensors and
    corresponding gradient vector coordinates applied to the I0-dataset.
 The program takes three parameters as input :
    a 1D file of the gradient vectors with lines of ASCII floats Gxi,Gyi,Gzi.
    Only the non-zero gradient vectors are included in this file (no G0 line).
 The I0 dataset is a volume without any gradient applied.
 The DT dataset is the 6-sub-brick dataset containing the diffusion tensor data,
    Dxx, Dxy, Dyy, Dxz, Dyz, Dzz (lower triangular row-wise order)

   -prefix pname    = Use 'pname' for the output dataset prefix name.
   -automask        = mask dataset so that the gradient images
                      are computed only for high-intensity (presumably
                      brain) voxels.  The intensity level is determined
                      the same way that 3dClipLevel works.

   -datum type      = output dataset type [float/short/byte]
                      (default is float).
   -help            = show this help screen.
   -scale_out_1000  = matches with 3dDWItoDT's '-scale_out_1000'
                      functionality.  If the option was used
                      there, then use it here, too.


    3dDTtoDWI -prefix DWI -automask tensor25.1D 'DT+orig[26]' DT+orig.

 The output is a n sub-brick bucket dataset containing computed DWI images.
    where n is the number of vectors in the gradient file + 1

This program accepts datasets that are modified on input according to the
following schemes:
  'r1+orig[3..5]'                                    {sub-brick selector}
  'r1+orig<100..200>'                                {sub-range selector}
  'r1+orig[3..5]<100..200>'                          {both selectors}
  '3dcalc( -a r1+orig -b r2+orig -expr 0.5*(a+b) )'  {calculation}