Abstract

A reconstruction algorithm for three-dimensional optical diffusion tomography is presented that uses Bayesian regularization and iterative coordinate descent optimization incorporating estimation of source-detector coupling coefficients. Simulations show that this is an accurate and efficient approach.

© 2001 Optical Society of America

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