Quality improvement of images with metal artifact reduction using a noise recovery technique in computed tomography

In metal artifact reduction (MAR) in computed tomography (CT) based on projection data inpainting, X-ray photon noise has not been considered in the inpainting process. This study aims to assess the effectiveness of a MAR technique incorporating noise recovery in such projection data regions, compared with existing MAR techniques based on projection data normalization (NMAR), including one with frequency splitting (FSNMAR). Phantoms simulating hip prostheses and dental fillings were scanned using a 64-row multi slice CT scanner. The projection data was processed by NMAR and NMAR with noise recovery (NRNMAR); the processed data was sent back to the CT system for reconstruction. For the phantoms and clinical cases with hip prostheses and dental fillings, images were reconstructed without MAR, and with NMAR, NRNMAR, and FSNMAR (incorporated in the CT system). To validate the efficacy of noise recovery, noise power spectra (NPSs) were measured from the images of the hip prosthesis phantom with and without metals. The artifact index (AI) was compared between NRNMAR and FSNMAR. The resultant NPSs of NRNMAR were very similar to those of phantom images with no metals, endorsing the efficacy of noise recovery. The NMAR images had unnatural noise textures and FSNMAR caused additional streaks. NRNMAR exhibited some significant improvements in these respects: It reduced the AI by as much as 66.2-88.6% compared to FSNMAR, except for the case of a unilateral prosthesis. In conclusion, NRNMAR, which simply adds white noise to the projection data, would be effective in improving the quality of CT images with metal artifacts reduction.