dtiTensor-methods {dti} | R Documentation |
The method estimates, in each voxel, the diffusion tensor from the DWI data contained in an object of class "dtiData"
.
## S4 method for signature 'dtiData': dtiTensor(object, method="nonlinear", varmethod="replicates", varmodel="local")
object |
Object of class "dtiData" |
method |
Method for tensor estimation. May be "linear" , or "nonlinear" . |
varmethod |
Specifies the method for estimating the error variance. May be "replicates" . |
varmodel |
Specifies the model for the variance. May be "global" , or "local" . |
An object of class "dtiTensor"
.
method=="linear"
estimates are obtained using a linearization of the tensor model. This was the estimate used in Tabelow et.al. (2008). method=="nonlinear"
uses a nonlinear regression model with reparametrization that ensures the tensor to be positive semidefinite, see Koay et.al. (2006). 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. If varmodel=="global"
a homogeneous variance is assumed and estimated as the median of the local variance estimates.
Karsten Tabelow tabelow@wias-berlin.de
J"org Polzehl polzehl@wias-berlin.de
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/
dtiData
,
readDWIdata
,
dtiIndices-methods
,
medinria
,
dtiData
,
dtiTensor
## Not run: demo(dti_art)