Three-dimensional Bayesian optical diffusion tomography: source-detector calibration

摘要

Optical diffusion tomography is a new imaging modality that offers significant potential in medical applications. The resulting nonlinear image reconstruction problem is further complicated by the fact that for practical imaging variable source excitation and detector coupling needs to be accounted for in order to obtain quantitative images. We formulated the joint problem of coupling coefficient estimation and three-dimensional image reconstruction in a Bayesian framework, and the resulting estimates are computed in an iterative coordinate-descent optimization scheme. Simulations show that this approach is an accurate and efficient method for simultaneous reconstruction of absorption and diffusion coefficients, as well as the coupling coefficients.