"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