A Normalized Metal Artifact Reduction Method Using an Artifact-Reduced Prior for Dental Computed Tomography

Abstract

In dental computed tomography (DCT), metal artifact reduction (MAR) is a critical issue to improve the clinical usefulness of DCT and remains a challenging problem. Although various MAR methods have been developed in medical CT, those methods may not work robustly in DCT because teeth themselves, as well as metallic objects, have high X-ray attenuation. In this study, we investigated an MAR method that was based on sinogram normalization interpolation with an artifact-reduced prior for DCT. The method consisted of three main steps: segmentation of a metal trace, generation of an artifact-reduced prior image, and sinogram completion followed by DCT reconstruction. We performed a computational simulation and performed an experiment on a teeth phantom with several metal inserts to validate the proposed method. With respect to the root-mean-square error and the structural similarity, we compared our results with the ones obtained by using the combined prior-based MAR (CP-MAR) method. Our results indicate that the proposed MAR method reduced metal artifacts considerably in DCT images and showed an image performance that was better than that obtained by using the state of the art method (CP-MAR) in reducing streak artifacts without introducing any contrast anomaly.