A feasibility study of metal artifacts reduction using weighted iterative reconstruction algorithm for frequency split metal artifact reduction

Abstract

The sinogram inpainting based methods such as normalized metal artifact reduction (NMAR) shows good performance in reducing the metal artifacts. However, these methods wipe away the structures near the metal which are severely corrupted by artifacts. The proposed method using a weight to lower metal corrupted pixels during the iteration instead of using an inpainting method to conserve the structures. Then, the proposed method was complementarily used with NMAR to generate a corrected image using the frequency split method. The titanium inserted XCAT phantoms were simulated from the 80kVp of energy. The metals were segmented from the filtered backprojection image using the threshold from the projection data. Afterwards, they were projected to acquire the metal sinogram index and the metal subtracted projection data. A weight map is generated from the scale factor and the log of the original raw data which has the metal index. The metal subtracted projection data were iteratively reconstructed. During the iteration, the step size of the update term was affected by a weight map, and the contributions of the metal present sinogram were lowered. Finally, using the frequency split approach, the corrected image was generated from the proposed and NMAR results. It was possible to lower the artifacts while conserving the structures in the proposed method. This work indicates the weighted iterative reconstruction can be complementarily used with the existing FSMAR approach.