基于压缩感知的稀疏扫描型CT图像快速重建算法  

Fast reconstruction algorithm of sparse scanning CT images based on compressed sensing

作　　者：董建 张海宁 Dong Jian;Zhang Haining(Tianjin Key Laboratory of Information Sensing and Intelligent Control,School of Automation and Electrical Engineering,Tianjin University of Technology and Education,Tianjin 300222,China)

机构地区：[1]天津职业技术师范大学自动化与电气工程学院、天津市信息传感与智能控制重点实验室,天津300222

出　　处：《国外电子测量技术》2024年第10期64-71,共8页Foreign Electronic Measurement Technology

基　　金：天津市教委科研计划项目(自然科学)(2021KJ012)资助。

摘　　要：鉴于X射线辐射对于患者存在的潜在风险,降低患者所受辐射剂量的问题已经引起了科研工作者的广泛关注。针对稀疏角度扫描型CT图像的重建方案提出了一种新的基于非线性压缩感知的图像重建算法。该算法将目标函数的正则化项引入了非线性滤波操作,并且使用联合双边滤波器,将其加入重建过程以获得图像质量的进一步提升。同时利用凸优化领域的临近点算法对目标函数进行最小化处理,构建出行加速型迭代算法。实验选用均方根误差(root mean square error,RMSE)和峰值信噪比(peak signal-to-noise ratio,PSNR)作为评价指标,将新算法同之前提出的3种算法进行对比,其峰值信噪比提升了5.75~6.33 dB,均方根误差降低了0.002~0.023。数字图像模型以及实际临床腹部影像的重建结果表明,新算法有效地去除了图像中的伪影噪声,同时最大限度保留了图像细节。In view of the potential risks of X-ray radiation to patients,the issue of reducing the radiation dose exposed by patients has attracted widespread attention among scientific researchers.This paper proposes a new image reconstruction algorithm based on nonlinear compressed sensing for the reconstruction scheme of sparse angle scan CT images.In this algorithm,the nonlinear filter is added to the regularization term of the cost function,and the joint bilateral filter is added to the reconstruction process to further improve the image quality.At the same time,the proximal point algorithm in the field of convex optimization is used to minimize the cost function and construct a row acceleration iterative algorithm.In the experiment,root mean square error(RMSE)and peak signal-to-noise ratio(PSNR)were selected as evaluation indexes,and the new algorithm was compared with the three algorithms proposed before.The peak signal to noise ratio is increased by 5.75~6.33 dB,and the root-mean-square error is reduced by 0.002~0.023.The results of digital image model and actual clinical abdominal image reconstruction show that the new algorithm can effectively remove the artifact noise in the image while preserving the image details to the maximum extent.

关 键 词：CT图像重建 压缩感知 联合双边滤波 凸优化 

分 类 号：TN911.73[电子电信—通信与信息系统]