Superiorized iteration algorithm for ct image simultaneous reconstruction and segmentation

. We propose a model for computed tomography (CT) image reconstruction and segmentation simultaneously, which can be applied to singleenergy spectral (traditional) CT (SECT) and dual-energy spectral CT (DECT) image reconstruction. It is difficult to solve the model due to the large scale of imaging system and the nonlinear forward projection of DECT. In order to deal with the model, a superiorized iteration algorithm is presented, which handles image segmentation and image reconstruction alternately. The two steps are combined by a superiorized perturbation step. The convergence of the iteration procedure is proved for SECT image reconstruction theoretically, and the convergence for DECT image reconstruction is investigated numerically. Experiments on various data are conducted. Comparisons with existing methods show that the proposed method is better quantitatively and visually.