Package: dti
Version: 1.4.2
Date: 2019-09-26
Title: Analysis of Diffusion Weighted Imaging (DWI) Data
Authors@R: c(person("Karsten", "Tabelow", role = c("aut", "cre"),
                    email = "karsten.tabelow@wias-berlin.de"),
             person("Joerg", "Polzehl", role = c("aut"),
                    email = "joerg.polzehl@wias-berlin.de"),
             person("Felix", "Anker", role = c("ctb")))
Author: Karsten Tabelow [aut, cre],
  Joerg Polzehl [aut],
  Felix Anker [ctb]
Maintainer: Karsten Tabelow <karsten.tabelow@wias-berlin.de>
Depends: R (>= 3.5.0), awsMethods (>= 1.1-1)
SystemRequirements: gsl
Imports: methods, parallel, adimpro (>= 0.9), rgl, oro.nifti (>=
        0.3.9), oro.dicom, gsl, quadprog
LazyData: TRUE
Description: 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.
License: GPL (>= 2)
Copyright: This package is Copyright (C) 2005-2019 Weierstrass
        Institute for Applied Analysis and Stochastics.
URL: http://www.wias-berlin.de/research/ats/imaging/
Suggests: covr
RoxygenNote: 6.1.0
NeedsCompilation: yes
Packaged: 2019-09-30 08:28:58 UTC; polzehl
Repository: CRAN
Date/Publication: 2019-09-30 09:10:03 UTC
