PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

TractoR: Magnetic resonance imaging and tractography with R. J.D. Clayden, S. Munoz Maniega, A.J. Storkey, M.D. King, M.E. Bastin, and C.A. Clark. TractoR: Magnetic resonance imaging and tractography with R. Journal of Statistical Software. In Press., 2011.
John Clayden, Susana Munoz Maniega, Amos Storkey, Martin King, Mark Bastin and Chris Clark
Journal of Statistical Software Volume 44, Number 8, 2011.


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 specic code for tting signal models to diusion MRI data and performing tractography, a technique for visualizing neural connectivity.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:8883
Deposited By:Amos Storkey
Deposited On:21 February 2012