Reads diffusion tensor (single, two-tensor, three-tensor or multitensor) data from the
standard input, computes the eigenvalues and eigenvectors of each tensor and outputs the
results to the standard output. For multiple-tensor data the program outputs the
eigensystem of each tensor. For each tensor the program outputs: {l_1, e_11, e_12, e_13,
l_2, e_21, e_22, e_33, l_3, e_31, e_32, e_33}, where l_1 >= l_2 >= l_3 and e_i = (e_i1,
e_i2, e_i3) is the eigenvector with eigenvalue l_i. For three-tensor data, for example,
the output contains thirty-six values per voxel.
EXAMPLES
Compute the eigensystem in each voxel of diffusion MRI data set SubjectA.Bfloat and store
the output in EigenA.Bdouble:
Compute the eigensystem 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) and "multitensor" (see multitenfit(1)). By default, the
program assumes that the input data contains a single diffusion tensor in each voxel. If
the input model is "multitensor", the program assumes a maximum of two tensors per voxel
unless told otherwise with the -maxcomponents option.
-maxcomponents <number>
The maximum number of tensor components in a voxel of the input data.
-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". See camino(1).
-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).