A field of view based metal artifact reduction method with the presence of data truncation

Abstract

In X-ray CT imaging, the metal objects produce significant beam hardening and streak artifacts in the reconstructed CT images. To reduce the metal artifacts, several sinogram inpainting based methods have been proposed, where projection data within the metal trace region of the sinogram are treated as missing, and estimated by interpolation. However, they generally assume data truncation does not occur and all metal objects reside inside the FOV. For small FOV imaging such as dental CT, these assumptions are violated, and thus using traditional inpainting based MAR would not be effective. In this work, we proposed a new MAR method to reduce the metal artifacts effectively when the metal objects reside outside the FOV for the small FOV imaging. The proposed method synthesizes the projection data of small FOV image by conducting forward projection, which is treated as the originally measured sinogram. Thus the effect of metal objects outside the FOV was minimized during the inpainting procedure. The performance of the proposed method is compared with the traditional linear MAR and NMAR. The results showed the effectiveness of the proposed method to reduce the residual artifacts, which were present in the traditional linear MAR and NMAR images.