Package dti details

Analysis of Diffusion Weighted Imaging (DWI) Data

Diffusion Weighted Imaging (DWI) 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. The functionality includes diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), modeling for high angular resolution diffusion weighted imaging (HARDI) using Q-ball-reconstruction and tensor mixture models, several methods for structural adaptive smoothing including POAS and msPOAS, and a streamline fiber tracking for tensor and tensor mixture models. The package provides functionality to manipulate and visualize results in 2D and 3D.

Maintainer: Karsten Tabelow < karsten.tabelow at >


From within R, enter citation('dti')


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  Versions(Pending - no previous version)
To install this package, start R and enter:


# Default Install

# from GitHub
neuro_install('dti', release = "stable", release_repo = "github")
neuro_install('dti', release = "current", release_repo = "github")

More detailed installation instructions can be found here.


Initially submitted on October 1 2018 4:57PM
Last updated on March 31 2021 10:00AM
Package type standard
Source GitHub GitHub
Neuroconductor GitHub GitHub
System requirementsgsl
DependsR (3.5.0), awsMethods(>=1.1-1)
Importsmethods, parallel, adimpro (0.9), aws (2.4.1), rgl, oro.nifti (0.3.9), oro.dicom, gsl, quadprog