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

Description

The method estimates, in each voxel, the diffusion tensor from the DWI data contained in an object of class "dtiData".

Usage

## S3 method for class 'dtiData':
dtiTensor(object, method=c( "nonlinear", "linear", "quasi-likelihood"), 
          sigma = NULL, L = 1, mc.cores = setCores( , reprt = FALSE))

Arguments

object

Object of class "dtiData"

method

Method for tensor estimation. May be "linear", or "nonlinear". method=="quasi-likelihood" solves the nonlinear regression problem with the expected value of the signal as regression function and weighting according

sigma

(local) scale parameter of the signal's distribution.

(local) effective degrees of freedom.

mc.cores

Number of cores to use. Defaults to number of threads specified for openMP, see documentation of package awsMethods. Our experience suggests to use 4-6 cores if available.

Value

An object of class "dtiTensor".

References

J. Polzehl and K. Tabelow, Beyond the diffusion tensor model: The package dti, Journal of Statistical Software, 44(12), 1-26 (2011).

K. Tabelow, H.U. Voss and J. Polzehl, Modeling the orientation distribution function by mixtures of angular central Gaussian distributions, Journal of Neuroscience Methods, 203(1), 200-211 (2012).

J. Polzehl and K. Tabelow, Structural adaptive smoothing in diffusion tensor imaging: The R package dti, Journal of Statistical Software, 31(9) 1-24 (2009). K. Tabelow, J. Polzehl, V. Spokoiny and H.U. Voss. Diffusion Tensor Imaging: Structural adaptive smoothing, NeuroImage 39(4), 1763-1773 (2008).

C.G. Koay, J.D. Carew, A.L. Alexander, P.J. Basser and M.E. Meyerand. Investigation of Anomalous Estimates of Tensor-Derived Quantities in Diffusion Tensor Imaging, Magnetic Resonance in Medicine, 2006, 55, 930-936.

http://www.wias-berlin.de/projects/matheon_a3/

Examples

Run this code

demo(dti_art)

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