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Proceedings Paper

A novel Riemannian metric for analyzing HARDI data
Author(s): Sentibaleng Ncube; Anuj Srivastava
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Paper Abstract

We propose a novel Riemannian framework for analyzing orientation distribution functions (ODFs) in HARDI data sets, for use in comparing, interpolating, averaging, and denoising ODFs. A recently used Fisher-Rao metric does not provide physically feasible solutions, and we suggest a modification that removes orientations from ODFs and treats them as separate variables. This way a comparison of any two ODFs is based on separate comparisons of their shapes and orientations. Furthermore, this provides an explicit orientation at each voxel for use in tractography. We demonstrate these ideas by computing geodesics between ODFs and Karcher means of ODFs, for both the original Fisher-Rao and the proposed framework.

Paper Details

Date Published: 11 March 2011
PDF: 7 pages
Proc. SPIE 7962, Medical Imaging 2011: Image Processing, 79620Q (11 March 2011); doi: 10.1117/12.878100
Show Author Affiliations
Sentibaleng Ncube, The Florida State Univ. (United States)
Anuj Srivastava, The Florida State Univ. (United States)

Published in SPIE Proceedings Vol. 7962:
Medical Imaging 2011: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

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