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An Introduction to Visualization of Diffusion Tensor Imaging and Its Applications

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Visualization and Processing of Tensor Fields

Part of the book series: Mathematics and Visualization ((MATHVISUAL))

Abstract

Water diffusion is anisotropic in organized tissues such as white matter and muscle. Diffusion tensor imaging (DTI), a non-invasive MR technique, measures water self-diffusion rates and thus gives an indication of the underlying tissue microstructure. The diffusion rate is often expressed by a second-order tensor. Insightful DTI visualization is challenging because of the multivariate nature and the complex spatial relationships in a diffusion tensor field. This chapter surveys the different visualization techniques that have been developed for DTI and compares their main characteristics and drawbacks. We also discuss some of the many biomedical applications in which DTI helps extend our understanding or improve clinical procedures. We conclude with an overview of open problems and research directions.

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Authors and Affiliations

  1. Department of Biomedical Engineering, Eindhoven University of Technology, WH 2.103, 5600 MB, Eindhoven, The Netherlands

    A. Vilanova

  2. Department of Computer Science, Brown University, 115 Waterman Street, Box 1910, Providence, RI, 02912, USA

    S. Zhang & D. Laidlaw

  3. School of Computing, University of Utah, 50 South Central Campus Drive, Salt Lake City, UT, 84112, USA

    G. Kindlmann

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Editors and Affiliations

  1. Faculty of Mathematics and Computer Science, Saarland University, Building 27, 66041, Saarbrücken, Germany

    Joachim Weickert

  2. Computer Graphics and Visualization Group, Technical University of Kaiserslautern, PO Box 3049, 67653, Kaiserslautern, Germany

    Hans Hagen

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Vilanova, A., Zhang, S., Kindlmann, G., Laidlaw, D. (2006). An Introduction to Visualization of Diffusion Tensor Imaging and Its Applications. In: Weickert, J., Hagen, H. (eds) Visualization and Processing of Tensor Fields. Mathematics and Visualization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-31272-2_7

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