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