基于增广拉格朗日的全变分正则化CT迭代重建算法  

Total Variation Regularization CT Iterative Reconstruction Algorithm Based on Augmented Lagrangian Method

作　　者：孝大宇[1] 郭洋 李建华[1] 康雁[1] XIAO Da-yu;GUO Yang;LI Jian-hua;KANG Yan(School of Sino-Dutch Biomedical ＆ Information Engineering,Northeastern University,Shenyang 110169,China.)

机构地区：[1]东北大学中荷生物医学与信息工程学院,辽宁沈阳110169

出　　处：《东北大学学报（自然科学版）》2018年第7期964-969,共6页Journal of Northeastern University(Natural Science)

基　　金：国家自然科学基金资助项目(61372014)

摘　　要：采用一种基于增广拉格朗日方法 (augmented Lagrangian method)求解全变分正则化(total variation regularization)算法(ALMTVR)来进行CT图像重建.将ALMTVR算法与经典的代数重建算法(algebraic reconstruction technique,ART)进行比较,并采用仿真数据与实际数据进行实验.在实验中,使用ALMTVR算法与ART算法分别进行图像重建,并对重建图像进行对比分析.实验结果表明:所提算法与ART算法相比,显著提高了图像重建的质量与速度,显示了其对图像重建的有效性及在CT成像系统中潜在的应用价值.A novel algorithm based on augmented Lagrangian method was presented to solve total variation regularization problem（ ALMTVR） of the CT iterative reconstruction. The classical algebraic reconstruction technique（ ART） was compared with the ALMTVR algorithm,the simulation data and actual data are used in the experiment. The ALMTVR algorithm and the ART algorithm were used to reconstruct the images respectively,and the reconstruction images were compared and analyzed. Results showed that,compared with ART algorithm,the proposed algorithm can significantly improve image quality and reconstruction speed,which indicates the proposed algorithm is effective and has potential applications in the CT imaging system.

关 键 词：CT迭代重建 增广拉格朗日方法 全变分正则化 仿真数据 实际投影数据 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]