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VISUALIZING NEURONAL STRUCTURES IN THE HUMAN BRAIN VIA DIFFUSION TENSOR MRI 

Authors: Werner Benger Dr. abc;  Hauke Bartsch d;  Hans-Christian Hege e;  Hagen Kitzler f;  Anna Shumilina g; Annett Werner f
Affiliations:   a Center for Computation & Technology, Louisiana State University, Baton Rouge, Louisiana, USA
b Zuse Institute Berlin (ZIB), Berlin-Dahlem, Germany
c Max-Planck Institute for Gravitational Physics, Potsdam, Germany
d Mercury Computer Systems, San Diego, California, USA
e Department of Visualization and Data Analysis, Zuse Institute Berlin (ZIB), Berlin-Dahlem, Germany
f Department of Neuroradiology, Dresden University of Technology, Dresden, Germany
g Department of Mathematics, Technical University of Berlin, Berlin, Germany
DOI: 10.1080/00207450500505977
Publication Frequency: 12 issues per year
Published in: journal International Journal of Neuroscience, Volume 116, Issue 4 April 2006 , pages 461 - 514
Subject: Neuroscience;
Formats available: HTML (English) : PDF (English)
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Abstract

Acquisition, analysis, and visualization of diffusion tensor magnetic resonance imaging (DT-MRI) is still an evolving technology. This article reviews the fundamentals of the data acquisition process and the pipeline leading to visual results that are interpretable by physicians in their clinical practice. The limitations of common approaches for visualizing the retrieved data are discussed and a new statistical method is presented to assess the reliability of the acquired tensor field. A novel visualization method is proposed which is discussed in light of neurophysiological considerations of the perception of colored patterns. It is argued that this method is more accurate for medical data while providing a nearly optimal visual stimulus. The method is evaluated on a patient study with a brain tumor.
Keywords: brain tumor study; diffusion-tensor imaging; model validation; neuroradiology; neurosurgery; pattern recognition; statistical analysis; tensor field visualization
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