中文摘要：

近年来CT成像技术在临床医学中广泛应用,但当病人体内含有金属移植物时,由于射线硬化等原因很可能在金属物体周围产生亮暗伪影,降低图像质量,影响诊断的准确性.为了消除CT图像中的金属伪影,本文提出基于Mean Shift和插值图像修复的算法,基本流程为用自适应Mean Shift算法预处理CT图像,平滑噪声和轻度伪影,用简化的Mean Shift算法快速精确分割金属物体,由修复组织信息的插值图像生成先验图像,用先验图像的投影数据替换原投影数据得到校正后的CT图像.经过对比实验,文中算法在去除金属伪影的同时,能够保护原有CT图像的组织结构,取得了更好的处理效果.

英文摘要：

In recent years,CT imaging technique has been widely used in clinical medicine domain. However for the patient with metallic implants,there is most likely bright and dark artifacts around metal objects due to beam hardening and other reasons,which will reduce the quality of the image and affect the accuracy of physician diagnosis. In order to reduce the metal artifacts in CT images,we address a method based on Mean Shift algorithm and interpolation image restoration algorithm in this paper,and the basic flowis as follows. Firstly,adaptive Mean Shift algorithm was used to smooth noise and the mild artifacts for preprocessing. Secondly,using Mean Shift simplified algorithm metal objects were segmented quickly and accurately. Thirdly,the prior image was generated by interpolated image with anatomical structures restoration,then the original projection data was replaced with the prior projection data to obtain the final corrected image. After the contrast experiment,the method in this paper not only removes metal artifacts remarkably but also protects the original anatomical structures,showing that our method achieves better appearance.