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.

muschellij2 badges: AppVeyor Build Status Travis build status Coverage status

The goal of dti is to provide tools to analysis of Diffusion Weighted Imaging (DWI) Data.


You can install dti from GitHub with:



Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


1.5.1 by Karsten Tabelow, 2 years ago

Browse source code at

Authors: Karsten Tabelow [aut, cre] , Joerg Polzehl [aut] , Felix Anker [ctb]

Documentation:   PDF Manual  

Task views:

GPL (>= 2) license

Imports methods, parallel, adimpro, aws, rgl, oro.nifti, oro.dicom, gsl, quadprog

Depends on awsMethods

Suggests covr

System requirements: gsl

See at CRAN