在计算机断层扫描 (CT)中，金属植入物会引入严重的伪影，导致图像质量降低影响诊断价值。为了对锥束CT中的金属伪影进行校正，提出了一种基于双调和方程的金属伪影校正算法。首先，对含金属伪影的重建图像进行双边滤波和金属阈值分割，获得金属和非金属图像；然后，对二者进行正向投影，获得金属投影区域和先验投影图像；接下来，利用先验投影图像对原始投影进行归一化，并对金属区域进行双调和方程插值修复，获得修复的投影数据；最后，对修复的投影数据去归一化,并利用FDK 算法进行重建，再与金属图像融合获得最终的校正图像。为了验证该算法的性能，采用实际拍摄的数据进行金属伪影校正实验。结果表明，与常用的线性插值校正算法和归一化校正算法相比，所提算法ROI区域内图像的均方根误差分别减少了22%和8%，有效地抑制了金属伪影，优于常用的去金属伪影算法。


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. 


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