White Matter Fiber Tractography via
Anisotropic Diffusion Simulation in the Human Brain

Ning Kang, Jun Zhang
Laboratory for High Performance Scientific Computing and Computer Simulation
Department of Computer Science
University of Kentucky
773 Anderson Hall
Lexington, KY 40506-0046, USA

and
Eric S. Carlson
Department of Chemical Engineering
University of Alabama
P. O. Box 870203
Tuscaloosa, AL 35487-0203, USA

and
Daniel Gembris
Institute for Computational Medicine
University of Mannheim
B6, 23-29C, D-68131 Mannheim, Germany

Abstract

A new approach for noninvasively tracing brain white matter fiber tracts is presented using diffusion tensor magnetic resonance imaging (DT-MRI) data. This technique is based on successive anisotropic diffusion simulations over the human brain, which are utilized to construct three dimensional diffusion fronts. The fiber pathways may then be determined by evaluating the distance and orientation from fronts to their corresponding diffusion seeds. Real DT-MRI data are employed to demonstrate the tracking scheme. It is shown that several major white matter fiber pathways can be reproduced noninvasively, with the tract branching being allowed. Since the diffusion simulation, which is truly a physical phenomenon reflecting the underlying architecture of cerebral tissues, makes full use of the entire diffusion tensor data instead of part of it, our proposed approach is expected to enhance robustness and reliability in white matter fiber reconstruction.


Key words: fiber tractography, anisotropic diffusion simulation, diffusion tensor magnetic resonance imaging

Mathematics Subject Classification:


Download the compressed postscript file kang4.ps.gz, or the PDF file kang4.pdf.
Technical Report No. 410-04, Department of Computer Science, University of Kentucky, Lexington, KY, 2004.

This research was supported in part by the U.S. National Science Foundation under the grant CCR-9988165, CCR-0092532, and ACR-0202934, in part by the U.S. Department of Energy Office of Science under grant DE-FG02-02ER45961, and in part by the University of Kentucky Research Committee.