Abstract: In computed tomography (CT), metal implants introduce severe artifacts, leading to degraded image quality and impacting diagnostic value. To correct metal artifacts in cone beam CT, a metal artifact correction algorithm based on the biharmonic equation is proposed. Firstly, the reconstructed image with metal artifacts is filtered using bilateral filtering and segmented using a metal threshold, obtaining metal and non-metal images. Secondly, forward projection is applied to both images, generating metal projection regions and prior projection images. Thirdly, the original projection is normalized using the prior projection image, and the metal regions are repaired using biharmonic equation interpolation, resulting in the repaired projection data. The repaired projection data is then denormalized and reconstructed using the FDK algorithm. Finally, the reconstructed image is fused with the metal image to obtain the final corrected image. To validate the performance of this algorithm, experiments on metal artifact correction were conducted using real acquired data. The results show that compared to commonly used linear interpolation and normalization correction algorithms, the root mean square errors within the region of interest (ROI) are reduced by 22% and 8% respectively. This algorithm effectively suppresses metal artifacts and outperforms commonly used metal artifact removal methods. 

Key words: cone beam CT, metal artifact correction, biharmonic equation interpolation, inpaint, normalization correction