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Proceedings Paper

Analysis of dynamic light scattering data with sparse Bayesian learning for the study of cataractogenesis
Author(s): Su-Long Nyeo; Rafat R. Ansari
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Paper Abstract

Dynamic light scattering (DLS) experimental data is statistical in nature and therefore requires a probabilistic analysis tool. The probabilistic sparse Bayesian learning (SBL) algorithm is introduced for analyzing DLS data from ocular lenses. The algorithm is used to reconstruct the most-relevant size distribution of the α-crystallins and their aggregates. The performance of the algorithm is evaluated by analyzing simulated data from a known distribution and experimental DLS data from the ocular lenses of several mammals.

Paper Details

Date Published: 3 March 2010
PDF: 8 pages
Proc. SPIE 7550, Ophthalmic Technologies XX, 75501R (3 March 2010); doi: 10.1117/12.846644
Show Author Affiliations
Su-Long Nyeo, National Cheng Kung Univ. (Taiwan)
Rafat R. Ansari, NASA Glenn Research Ctr. (United States)


Published in SPIE Proceedings Vol. 7550:
Ophthalmic Technologies XX
Fabrice Manns; Per G. Söderberg; Arthur Ho, Editor(s)

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