neuroconductor/dti: 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.

Getting started

Package details

AuthorKarsten Tabelow [aut, cre], Joerg Polzehl [aut], Felix Anker [ctb]
MaintainerKarsten Tabelow <karsten.tabelow@wias-berlin.de>
LicenseGPL (>= 2)
Version1.5.2
URL http://www.wias-berlin.de/research/ats/imaging/
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("neuroconductor/dti")
neuroconductor/dti documentation built on May 20, 2021, 4:28 p.m.