"dtiData"
-object is provided). It also implements structural adaptive smoothing of a diffusion tensor using a Riemannian metric (in case a "dtiTensor"
-object is given), although we strictly recommend to use the first variant due to methodological reasons.## S3 method for class 'dtiData':
dti.smooth(object, hmax=5, hinit=NULL, lambda=20, tau=10, rho=1, graph=FALSE, slice=NULL, quant=.8, minanindex=NULL, hsig=2.5, lseq=NULL, method="nonlinear", varmethod="residuals", rician=TRUE, niter=5, varmodel="local",result="Tensor")
"dtiData"
or an object of class "dtiTensor"
minanindex
as corresponding quantile of FA if is.null(minanindex)
lambda
"linear"
, "nonlinear"
varmethod=="replicates"
, or "residuals"
."global"
, or "local"
."Tensor"
for create a dtiTensor-object and "dtiData"
for a dtiData-object containing a smoothed data cube.dtiTensor
.Koay, C. G. and Carew, J. D. and Alexander, A. L. and Basser, P. J. and Meyerand, M.E. (2006) Investigation of Anomalous Estimates of Tensor-Derived Quantities in Diffusion Tensor Imaging, Magnetic Resonance in Medicine 55, 930--936.
dtiData
,
readDWIdata
,
dtiTensor-methods
,
dtiIndices-methods
,
medinria
,
dtiData
,
dtiTensor
,
dtiIndices