基于有序子集的惩罚加权最小二乘低剂量CT优质重建算法研究  

High quality reconstruction of low-dose computed tomography based on ordered subsets penalized weighted least-squares

作　　者：林少春[1] 马建华[1] 陈武凡[1] 

机构地区：[1]南方医科大学生物医学工程学院,广东省广州市510515

出　　处：《中国组织工程研究与临床康复》2008年第4期679-682,共4页Journal of Clinical Rehabilitative Tissue Engineering Research

基　　金：国家"九七三"重点基础研究发展规划项目(2003CB716101)~~

摘　　要：为解决低剂量CT图像重建的噪声问题,在经典的加权最小二乘迭代算法的基础上,采用有序子集设计策略,针对此问题进行低剂量CT图像优质重建。有序子集技术下惩罚加权最小二乘算法,可以较有效处理低剂量条件下CT重建信息量不足带来的缺点。同时有序子集的引入,使得新算法较经典的惩罚加权最小二乘算法在速度上得到很大提高,低剂量CT的重建图像仍可保持较佳的图像质量和较高的空间分辨率。To solve the noise problem about image reconstruction of the low-dose CT. It investigates ordered subsets to the classical method of penalized weighted least-squares （OS-PWLS） to address this problem. Low dose CT information can be processed effectively improved by the OS-PWLS algorithm under less sample information. Because of the introduction of the Ordered Subsets, our proposed method enhances the speed effectively, and keeps the high quality image and perfect spatial resolution in the low-dose CT reconstruction.

关 键 词：低剂量CT 图像重建 有序子集 惩罚加权最小二乘法 

分 类 号：R318[医药卫生—生物医学工程]