Nested Loop Algorithm for Parallel Model Based Iterative Reconstruction

Model based iterative reconstruction (MBIR) algorithms have been used in clinical studies to allow significant dose reduction in CT scans while maintaining the diagnostic image quality. Simultaneous-update algorithms, which can take advantage of massively parallel computer architectures, are promising to significantly improve the speed of MBIR. To achieve this goal, we also need to improve the convergence speed of these algorithms. In this paper, we propose a fast converging simultaneous-update algorithm using a nested loop structure. Preliminary experimental results show that the proposed algorithm has faster convergence speed compared to algorithms such as conjugate gradient and preconditioned conjugate gradient methods.