dtiTensor {dti}R Documentation

Estimate the diffusion tensor from DWI data

Description

generic function that estimates, in each voxel, the diffusion tensor from the DWI data contained in an object of class dtiData.

Usage

dtiTensor(object, ...)

Arguments

object object of class dtiData
... Additional arguments specifying the model
method
if model=="linear" estimates are obtained using a linearization of the tensor model. This was the estimate used in Tabelow et.al. (2008). model=="nonlinear" uses a nonlinear regression model with reparametrization that ensures the tensor to be positive semidefinite, see Koay et.al. (2006).
varmethod
specifies the method for estimating the error variance. If varmethod=="replicates" the error variance is estimated from replicated gradient directions if possible. Otherwise an estimate is obtained from the residual sum of squares.
varmodel
if varmodel=="global" a homogeneous variance estimate is assumed and estimated as the median of the local variance estimates.

Value

an object of class dtiTensor.

Author(s)

Karsten Tabelow tabelow@wias-berlin.de, Joerg Polzehl polzehl@wias-berlin.de

References

K. Tabelow, J. Polzehl, H.U. Voss, and V. Spokoiny. 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/

See Also

dtiData, dtiIndices, medinria2tensor, tensor2medinria, dtiData, dtiIndices

Examples

## Not run: demo(dti_art)

[Package dti version 0.5-4 Index]