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• 图像处理与计算机视觉 • 上一篇    下一篇

一种基于先验图像的锥束CT 金属伪影校正算法

  

  1. (1. 中国科学院苏州生物医学工程技术研究所医学影像技术研究室，江苏 苏州 215163；
    2. 南京理工大学电子工程与光电技术学院，江苏 南京 210094)
  • 出版日期:2020-08-31 发布日期:2020-08-22
  • 基金资助:
    国家自然科学基金项目(61801475)；中国博士后科学基金项目(2018M642320)；江苏省博士后科研资助项目(2018K180C)；中科院苏州
    医工所自主部署项目(Y95K091K05)；天津市科技计划项目(19YDYGHZ00030)

A prior-image-based metal artifact reduction method for cone beam CT

  1. (1. Medical Imaging Department, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou Jiangsu 215163, China;
    2. School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing Jiangsu 210094, China)
  • Online:2020-08-31 Published:2020-08-22
  • Supported by:
    National Natural Science Foundation of China (61801475); China Postdoctoral Science Foundation (2018M642320); Jiangsu Planned
    Projects for Postdoctoral Research Funds (2018K180C); Suzhou Institute of Biomedical Engineering and Technology (CAS) Planned
    Projects (Y95K091K05); Science and Technology Plan Projects of Tianjing (19YDYGHZ00030)

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摘要： 为了有效抑制锥束CT(CBCT)重建中金属植入物引入的伪影，提出一种基于先验
图像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、金属阈值分割、组织
聚类等预处理，获得金属图像和不含金属信息的先验图像；再对二者正向投影，获得金属投影
区域和先验投影数据；而后利用先验投影数据及金属边界邻域的投影数据对金属投影区域插值，
获得修复的投影数据；最后利用FDK 算法对修复的投影数据重建，并将其与金属图像融合，获
得最终的校正图像。为了验证该算法的性能，利用三维Shepp-Logan 头部模型数据和临床头部
CT 数据开展金属伪影校正实验，结果表明：与常用的线性插值算法和图像修补算法相比，该算
法的校正图像均方根误差最小、峰值信噪比最大。这说明该算法在有效保留图像边缘信息的同
时，可有效地抑制金属伪影。

关键词: 锥束CT, 金属伪影校正, 双边滤波, 先验图像, 插值

Abstract: To effectively suppress the artifacts caused by metal implants in the reconstruction process
of cone beam CT (CBCT) image, a prior-image-based metal artifact reduction method was proposed.
Firstly, the reconstructed image with metal artifacts was preprocessed by bilateral filtering, metal
threshold segmentation and tissue clustering to produce the metal image and the prior image without
metal information. Secondly, the metal image and prior image were respectively forward-projected to
produce the metal projection region and prior projection data. Then, the metal projection region was
interpolated by the prior projection data and the metal neighborhood projection data to produce the restored projection data. Finally, the CT image was reconstructed by the FDK algorithm and was
fused with the metal image to produce the final corrected image. To verify the performance of the
proposed algorithm, the metal artifact reduction experiments were carried out on the 3D Shepp-Logan
head phantom and clinical head CT data. The experimental results show that compared with the
commonly used linear-interpolation-based method and image-inpainting-based method, the corrected
image of the proposed method can keep the root-mean-square error to the minimum and the peak
signal-to-noise ratio to the maximum. This indicates that the proposed method can effectively
suppress metal artifacts while preserving image edge information.

Key words: cone beam CT, metal artifact reduction, bilateral filtering, prior image, interpolation