Metal artifact reduction by projection replacements and non-local prior image integration

Abstract

Abstract The presence of high-density objects remains an open problem in medical CT imaging. Data of projections that passing through such objects are dominated by noise. Reconstructed images become less diagnostically conclusive because of pronounced artifacts that manifest as dark and bright streaks. A new reconstruction algorithm is proposed, which incorporates information gained from a prior image. Based on a non-local regularization, these information are used to reduce streaking artifacts. In an iterative scheme, the prior image is transformed in order to match intermediate results of the reconstruction by solving a registration problem. During iterations, temporally appearing artifacts are reduced with a bilateral filter and projection values passing through high-density objects are replaced by new calculated values, which are used further on for the reconstruction. Results show that the proposed algorithm significantly reduces streaking artifacts.