Fast reconstruction of Bayesian iterative approximation in passive gamma-ray tomography

Median root prior expectation maximization (MRPEM) algorithm that belongs to the Bayesian iterative approximation is used in passive gamma emission tomography (GET) to reconstruct passive gamma emitter distribution. The algorithm converges slowly and may involve iterations of 50-200. Fast processing of the algorithm was integrated into MRPEM to accelerate the convergence. Then, the integrated MRPEM reconstructed a passive distribution of gamma emissions within a mock-up boiling water reactor (BWR) assembly. It was found that the reconstructions in GET using the integrated MRPEM could result in a 20% reduction in the mean absolute error (MAE) compared to the standard MRPEM.