TractoR : Magnetic Resonance Imaging and Tractography with R

Statistical techniques play a major role in contemporary methods for analyzing magnetic resonance imaging (MRI) data. In addition to the central role that classical statistical methods play in research using MRI, statistical modeling and machine learning techniques are key to many modern data analys...

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Bibliographic Details
Published in:Journal of statistical software 2011-10, Vol.44 (8)
Main Authors: Clayden, Jonathan D., Maniega, Susana Muñoz, Storkey, Amos J., King, Martin D., Bastin, Mark E., Clark, Chris A.
Format: Article
Language:English
Subjects:
diffusion
image processing
machine learning
magnetic resonance imaging
tractography
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Summary:Statistical techniques play a major role in contemporary methods for analyzing magnetic resonance imaging (MRI) data. In addition to the central role that classical statistical methods play in research using MRI, statistical modeling and machine learning techniques are key to many modern data analysis pipelines. Applications for these techniques cover a broad spectrum of research, including many preclinical and clinical studies, and in some cases these methods are working their way into widespread routine use. In this manuscript we describe a software tool called TractoR (for “Tractography with R”), a collection of packages for the R language and environment, along with additional infrastructure for straightforwardly performing common image processing tasks. TractoR provides general purpose functions for reading, writing and manipulating MR images, as well as more specific code for fitting signal models to diffusion MRI data and performing tractography, a technique for visualizing neural connectivity.
ISSN:1548-7660
1548-7660
DOI:10.18637/jss.v044.i08