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Authors: Jörg Polzehl, Karsten Tabelow
Title: [download]
(2737)
Beyond the Gaussian Model in Diffusion-Weighted Imaging: The Package dti
Reference: Vol. 44, Issue 12, Oct 2011
Submitted 2010-11-10, Accepted 2011-06-15
Type: Article
Abstract:

Diffusion weighted imaging (DWI) is a magnetic resonance (MR) based method to investigate water diffusion in tissue like the human brain. Inference focuses on integral properties of the tissue microstructure. The acquired data are usually modeled using the diffusion tensor model, a three-dimensional Gaussian model for the diffusion process. Since the homogeneity assumption behind this model is not valid in large portion of the brain voxel more sophisticated approaches have been developed.
This paper describes the R package dti. The package offers capabilities for the analysis of diffusion weighted MR experiments. Here, we focus on recent extensions of the package, for example models for high angular resolution diffusion weighted imaging (HARDI) data, including Q-ball imaging and tensor mixture models, and fiber tracking. We provide a detailed description of the package structure and functionality. Examples are used to guide the reader through a typical analysis using the package. Data sets and R scripts used are available as electronic supplements.

Paper: [download]
(2737)
Beyond the Gaussian Model in Diffusion-Weighted Imaging: The Package dti
(application/pdf, 2.9 MB)
Supplements: [download]
(530)
dti_0.9-6.3.tar.gz: R source package
(application/x-gzip, 482.1 KB)
[download]
(500)
v44i12.R: R example code from the paper
(application/octet-stream, 8.4 KB)
[download]
(536)
v44i12-data.zip: Data files
(application/zip, 44.3 MB)
Resources: BibTeX | OAI
Creative Commons License
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3)
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