Bayesian reconstruction of fluorescent molecular tomography via iteration of measurements.

Abstract

Fluorescent molecular tomography (FMT) is an important molecular imaging technique for medical diagnosis and treatment. In FMT, a typical forward model is the diffusion approximation. However, this approximation is not valid in biological tissues with low-scattering regions. To overcome this problem, a Bayesian method in combination with the model error is proposed. Further, an iteration method of boundary measurements is incorporated into the reconstruction process to improve the efficiency of reconstruction for FMT. Simulation results obtained demonstrate that the proposed approach can effectively improve the quality of the reconstructed results and speed up the reconstruction process.