Information-theoretic analysis of brain white matter fiber orientation distribution functions

Chiang, M. C., Klunder, A. D., McMahon, K., de Zubicaray, G. I., Wright, M. J., Toga, A. W., & Thompson, P. M. (2007) Information-theoretic analysis of brain white matter fiber orientation distribution functions. In Karssemeijer, Nico & Lelieveldt, Boudewijn (Eds.) Information Processing in Medical Imaging: 20th International Conference, IPMI 2007, Kerkrade, The Netherlands, July 2-6, 2007. Proceedings, Springer Berlin Heidelberg, Kerkrade, The Netherlands, pp. 172-182.

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We propose a new information-theoretic metric, the symmetric Kullback-Leibler divergence (sKL-divergence), to measure the difference between two water diffusivity profiles in high angular resolution diffusion imaging (HARDI). Water diffusivity profiles are modeled as probability density functions on the unit sphere, and the sKL-divergence is computed from a spherical harmonic series, which greatly reduces computational complexity. Adjustment of the orientation of diffusivity functions is essential when the image is being warped, so we propose a fast algorithm to determine the principal direction of diffusivity functions using principal component analysis (PCA). We compare sKL-divergence with other inner-product based cost functions using synthetic samples and real HARDI data, and show that the sKL-divergence is highly sensitive in detecting small differences between two diffusivity profiles and therefore shows promise for applications in the nonlinear registration and multisubject statistical analysis of HARDI data.

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5 citations in Scopus
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8 citations in Web of Science®

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ID Code: 85704
Item Type: Conference Paper
Refereed: Yes
DOI: 10.1007/978-3-540-73273-0_15
ISBN: 9783540732730
ISSN: 0302-9743
Divisions: Current > QUT Faculties and Divisions > Faculty of Health
Current > Institutes > Institute of Health and Biomedical Innovation
Copyright Owner: Copyright 2007 Springer-Verlag Berlin Heidelberg
Deposited On: 21 Oct 2015 01:34
Last Modified: 29 Oct 2015 04:30

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