dMRI-Lab 1.0
atti2artpp.m File Reference

Functions

function atti2artpp (in dwifile, in gifile, in bifile, in rtppfile, in varargin)
 

Function Documentation

◆ atti2artpp()

function atti2artpp ( in dwifile,
in gifile,
in bifile,
in rtppfile,
in varargin )

Computes the (apparent) Return To Plane Probability according to a mono-exponential model for single-shell acquisitions as described in AMURA:

                               atti(u,b) = exp(-b*D_0(u)),

where D_0(u) is the Apparent Diffusion Coefficient measured at b=b0 for each direction 'u' within the unit sphere.

Parameters
dwifileA string specifying the file containing the diffusion-weighted images.
gifileA string specifying the file containing the gradient directions.
bifileA string specifying the the corresponding b-values of each entry in gi.
Note
for the AMURA model to make sense, all bi should be similar, otherwise the sampling scheme is a multi-shell and a differente model (such as MiSFIT) should be used. Alternatively, bi can be a single scalar describing the acquired shell.
Parameters
rtppfileA string specifying the file to save the computed RTPP.
vararginOptional arguments passed as -name value pairs.
Returns
- rtopfile: The computed RTOP.

Mandatory Inputs:

  • dwifile: A string specifying the file containing the diffusion-weighted images.
  • gifile: A string specifying the file containing the gradient directions.
  • bifile: A string specifying the file containing the b-values.
  • rtppfile: A string specifying the file to save the computed RTPP.
  • varargin: Optional arguments passed as -name value pairs.

Optional Arguments - General parameters:

  • mask: a MxNxP array of logicals. Only those voxels where mask is true are processed, the others are filled with zeros (default: all trues).

Parameters related to SH computations:

  • tensor: wether (true) or not (false) using a tensor model instead of a model-free ODF estimation to compute the maximum diffusion direction. Using a tensor estimation is usually more robust (default: true).
  • lambda: the Laplace-Beltrami regularization parameter for the linear least squares problem of fitting SH coefficients (
    Note
    the order L used for SH is internally computed) (default 0.001).
    Sanity checks on the attenuation signal:
  • tl, tu: the lower and upper thresholds, respectively, defining the range the atti will lay within, so that tl should be close to 0 and tu should be close to 1 (default: 1.0e-7, 1-1.0e-7).

Advanced parameters:

  • tau: 1x1, the effective diffusion time of the dMRI sequence in miliseconds (default: 70.0e-3).
  • chunksz: the evaluation of SH at desired directions is done by repeatedly calling GenerateSHMatrix. This is done chunk-by-chunk for efficiency (default: 256).
  • clean: 1x1 double in the range [0,100]. This is a simple outlier rejection parameter to avoid out-of-range values: 0 means no outlier rejection is applied; >0 means outlier rejection is applied, the closer to 100 the more agressive (default: 50).

Example:

atti2artpp dwifile.nii gifile.bvec bifile.bval rtppfile.nii -mask mask_file.nii
function atti2artpp(in dwifile, in gifile, in bifile, in rtppfile, in varargin)
See also
atti2artpp