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dti (version 0.5-4)

DTI Analysis

Description

Diffusion Weighted Imaging is a Magnetic Resonance Imaging modality, that measures diffusion of water in tissues like the human brain. The package contains R-functions to process diffusion-weighted data in the context of the diffusion tensor model (DTI). This includes the calculation of anisotropy measures and, most important, the implementation of our structural adaptive smoothing algorithm as described in K. Tabelow, J. Polzehl, V. Spokoiny, and H.U. Voss, Diffusion Tensor Imaging: Structural Adaptive Smoothing, Neuroimage 39(4), 1763-1773 (2008).

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Version

Install

install.packages('dti')

Monthly Downloads

448

Version

0.5-4

License

GPL (>=2)

Maintainer

Karsten Tabelow

Last Published

September 26th, 2024

Functions in dti (0.5-4)

dti-class

Class "dti"
dtiTensor

Estimate the diffusion tensor from DWI data
summary

generic function for objects of class "dti", "dtiData", "dtiTensor" and "dtiIndices".
dtiTensor-class

Class "dtiTensor"
dtiIndices-class

Class "dtiIndices"
tensor2medinria

Write Tensor-Data as NIFTI File
dtiIndices

Create estimates of anisotropy indices from diffusion tensors
dtiData

Creates a dtiData object
plot

Visualizing of dtiIndices
dti.smooth

Smoothing of DWI data (Diffusion tensor model)
medinria2tensor

Read Tensor-Data from NIFTI File
dtiData-class

Class "dtiData"
print

generic function for objects of class "dti", "dtiData", "dtiTensor" and "dtiIndices".