%0 Journal Article
%T Study on Ordered Subsets-least Square Reconstruction of Image<br>有序子集最小二乘OS—LS图像重建迭代算法
%A LIU Li
%A YIN Yin
%A SHAN Bao-ci
%A LIU Li
%A YIN Yin
%A SHAN Bao-ci
%A LIU Li
%A YIN Yin
%A SHAN Bao-ci
%A <br>刘力
%A 印胤
%A 单保慈
%J 中国图象图形学报
%D 2005
%I 
%X In order to construct a new practical and fast iterative image reconstruction method, the ordered subsets(OS) technique is combined with the least square(LS) reconstruction of images in medical tomography. Reconstruction of simulated data and real positron emission tomography(PET) data shows that so accelerated OS-LS iterative image reconstruction method has a rapid convergent speed and higher spatial resolution. The reconstructed image quality and convergence speed by different subsets order are studied. As compared to the traditional LS reconstruction, OS-LS is L times faster, where L is the number of subsets, and the reconstructed images by OS-LS are better than the conventional FBP (filtered back-projection) as well. The conclusion is that the so proposed OS-LS reconstruction method can be used in real PET image reconstruction.
%K computer image processing
%K image reconstruction
%K subsets<br>图像重建
%K 迭代算法
%K 最小二乘
%K 子集
%K OS
%K 有序
%K Phantom
%K 收敛速度
%K 图像质量
%K 正电子发射
%K 滤波反投影
%K 重建方法
%K 技术应用
%K 模型数据
%K 分析比较
%K 计算时间
%K LS算法
%K 成像仪
%K PET
%K 传统
%K 仿真
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D06194629680C940ACE75262F54B9D85&aid=ACCFC018CC8288DA&yid=2DD7160C83D0ACED&vid=F3090AE9B60B7ED1&iid=94C357A881DFC066&sid=3EABEBD973E45554&eid=7E2D9DFE40003B3F&journal_id=1006-8961&journal_name=中国图象图形学报&referenced_num=1&reference_num=6