Reads diffusion tensor (single, two-tensor or three-tensor) data from the standard input,
computes the trace of each tensor, i.e., three times the mean diffusivity, and outputs
the results to the standard output. For multiple-tensor data the program outputs the
trace of each tensor, so for three-tensor data, for example, the output contains three
values per voxel.
Divide the output by three to get the mean diffusivity.
EXAMPLES
Compute Tr(D) in each voxel of diffusion MRI data set SubjectA.Bfloat and store the
output in TrD_A.Bdouble:
Compute Tr(D) for 10000 independent trials of fitting the diffusion tensor to data
synthesized from test function 1 (see datasynth(1)) using imaging scheme A.scheme and
assuming signal to noise ratio of 16 at b=0:
Specifies the model that the input data contains parameters for. Possible model types
are: "dt" (diffusion-tensor data), "twotensor" (two-tensor data), "threetensor"
(three-tensor data). By default, the program assumes that the input data contains a
single diffusion tensor in each voxel.
-inputdatatype <data type of input>
Specifies the data type of the input file. The data type can be any of the following
strings: "char", "short", "int", "long", "float" or "double".
-outputdatatype <data type of output>
Specifies the data type of the output data. The data type can be any of the following
strings: "char", "short", "int", "long", "float" or "double". See camino(1).