An iterative image reconstruction algorithm combined with forward and backward diffusion filtering for in-line X-ray phase-contrast computed tomography

Abstract

In-line X-ray phase-contrast computed tomography (IL-PCCT) can reveal fine inner structures for low-Z materials (e.g. biological soft tissues), and shows high potential to become clinically applicable. Typically, IL-PCCT utilizes filtered back-projection (FBP) as the standard reconstruction algorithm. However, the FBP algorithm requires a large amount of projection data, and subsequently a large radiation dose is needed to reconstruct a high-quality image, which hampers its clinical application in IL-PCCT. In this study, an iterative reconstruction algorithm for IL-PCCT was proposed by combining the simultaneous algebraic reconstruction technique (SART) with eight-neighbour forward and backward (FAB8) diffusion filtering, and the reconstruction was performed using the Shepp–Logan phantom simulation and a real synchrotron IL-PCCT experiment. The results showed that the proposed algorithm was able to produce high-quality computed tomography images from few-view projections while improving the convergence rate of the computed tomography reconstruction, indicating that the proposed algorithm is an effective method of dose reduction for IL-PCCT.