Regularized polychromatic reconstruction for transmission tomography

A polychromatic reconstruction algorithm that accounts for the exact physical model of transmission tomography is presented. Based on the equivalence between the Poisson log-likelihood function and the I-divergence, we derived a fast convergencing algorithm with a pixel-wise updating scheme, which is an extended version of the AM-ICD algorithm. The objective function in each iteration consists of approximated I-divergence and the generalized Gaussian Markov random field (GGMRF) model based regularization term for preventing diverging due to additive noise and the approximation of I-divergence. In a simulation study, we observed that the beam hardening artifact was significantly reduced in the extended AM-ICD algorithm with the use of a reasonable number of iterations. In addition, the proposed algorithm also showed reliable reconstruction results even for low dose conditions.