dti (version 0.9-3.1)

dwiMixtensor-methods: Methods for Function `dwiMixtensor' in Package `dti'

Description

The method estimates, in each voxel, a mixture of radial symmetric tensors from the DWI data contained in an object of class "dtiData".

Usage

## S3 method for class 'dtiData':
dwiMixtensor(object, maxcomp=3,  p=40, method="mixtensor", reltol=1e-6,
          maxit=5000, ngc=1000, optmethod="BFGS",nguess=100*maxcomp^2,
          msc="BIC")

Arguments

object

Object of class "dtiData"

maxcomp

Maximal number of mixture components.

p

Exponent in Jian-Model (only effective if method="Jian"(Not yet implemented)

method

Specifies the mixture model used. method="mixtensor" specifies a mixture of tensor models (default), method="Jian" refers to the model defined in Jian et al. (2007) with fixed p

reltol

Relative tolerance for Rs nmmin() function.

maxit

Maximal number of iterations in Rs nmmin() function.

ngc

provide information on number of voxel processed, elapsed time and estimated remaining time after ngc voxel.

optmethod

Optimization method used, currently available is optmethod="Nelder-Mead", optmethod="BFGS" using analytic gradients will be added

nguess

number of guesses in search for initial estimates

msc

Criterion used to select the order of the mixture model, either BIC (Bayes Information Criterion) AIC (Akaike Information Criterion) or AICC ((Bias-)Corrected Akaike Information Criterion)

Value

• An object of class "dwiMixtensor".

Details

The method estimates, in each voxel, a mixture of radial symmetric tensors from the DWI data contained in an object of class "dtiData". The number of mixture components is selected depending on the data, with a maximum number of components specified by maxcomp.

If method="Jian" the model parameters from Jian et al. (2007) with fixed p are estimated. With method="Jian2" also p is estimated.

In a voxel tensors are restricted to be rotational sysmmetric with common excentricity and destinct largest eigenvalue.

References

Jian et al. (2007), A novel tensor distribution model for the diffusion-weighted MR signal, NeuroImage 37, 164--176.

See Also

dtiData, readDWIdata, medinria, dtiData, dwiMixtensor

Examples

demo(mixtens_art)