Bayesian optical diffusion imaging

Jong Chul Ye; Charles A. Bouman; Kevin J. Webb; Rick P. Millane

doi:10.1117/12.351329

25 June 1999 Bayesian optical diffusion imaging

Jong Chul Ye, Charles A. Bouman, Kevin J. Webb, Rick P. Millane

Proceedings Volume 3816, Mathematical Modeling, Bayesian Estimation, and Inverse Problems; (1999) https://doi.org/10.1117/12.351329
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1999, Denver, CO, United States

Abstract

Frequency-domain diffusion imaging is a new imaging modality which uses the magnitude and phase of modulated light propagation through a highly scattering medium to reconstruct an image of the scattering and/or the absorption coefficient in the medium. In this paper, the inversion algorithm is formulated in a Bayesian framework and an efficient optimization technique is presented for calculating the maximum a posteriori image. Numerical result show that the Bayesian framework with the new optimization scheme out-performs conventional approaches in both speed and reconstruction quality.

Citation Download Citation

Jong Chul Ye, Charles A. Bouman, Kevin J. Webb, and Rick P. Millane "Bayesian optical diffusion imaging", Proc. SPIE 3816, Mathematical Modeling, Bayesian Estimation, and Inverse Problems, (25 June 1999); https://doi.org/10.1117/12.351329

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