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Proceedings Paper

3D modeling and segmentation of diffusion weighted MRI data
Author(s): Leonid Zhukov; Ken Museth; David E. Breen; Ross T. Whitaker
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Paper Abstract

Diffusion weighted magnetic resonance imaging (DW MRI) is a technique that measures the diffusion properties of water molecules to produce a tensor-valued volume dataset. Because water molecules can diffuse more easily along fiber tracts, for example in the brain, rather than across them, diffusion is anisotropic and can be used for segmentation. Segmentation requires the identification of regions with different diffusion properties. In this paper we propose a new set of rotationally invariant diffusion measures which may be used to map the tensor data into a scalar representation. Our invariants may be rapidly computed because they do not require the calculation of eigenvalues. We use these invariants to analyze a 3D DW MRI scan of a human head and build geometric models corresponding to isotropic and anisotropic regions. We then utilize the models to perform quantitative analysis of these regions, for example calculating their surface area and volume.

Paper Details

Date Published: 28 May 2001
PDF: 12 pages
Proc. SPIE 4319, Medical Imaging 2001: Visualization, Display, and Image-Guided Procedures, (28 May 2001); doi: 10.1117/12.428081
Show Author Affiliations
Leonid Zhukov, California Institute of Technology (United States)
Ken Museth, California Institute of Technology (United States)
David E. Breen, California Institute of Technology (United States)
Ross T. Whitaker, Univ. of Utah (United States)

Published in SPIE Proceedings Vol. 4319:
Medical Imaging 2001: Visualization, Display, and Image-Guided Procedures
Seong Ki Mun, Editor(s)

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