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

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.