PET Reconstruction Based on Optimal Linear Stochastic Filtering

摘要：

　　It turns out that the iterative approach is very attractive for image reconstruction in positron emission tomography(PET).Its reconstruction quality heavily depends on the accuracy of the measurement model,which consists of the projection matrix and the statistics of noise.Almost all of iterative approaches require that the projection matrix is exactly known a prior,which conflicts with the fact that it is impossible to obtain the exact projection matrix subject to a number of complicated and physical effects.Hence,in the paper we establish a more general measurement model where the projection matrix is disturbed by a Ganssian noise and provide a different PET reconstruction approach.It is based on the linear optimal filtering for stochastic system with multiplicative noise.The approach reconstructs the PET image effectively,whose performance is evaluated with the computer-synthesized Zubal-thorax-phantom.

关键词： PET image reconstruction filtering stochastic system

作者: WANG Hongxia CHEN Xin YU Li

作者单位: Department of Automation,Zhejiang University of Technology,Hangzhou,310023,P.R.China

会议类型: 国际会议

会议名称: The 33th Chinese Control Conference第33届中国控制会议

会议地点: 南京

会议语种:英文

页码: 5387-5391

在线出版日期: 2014-07-28（万方平台首次上网日期，不代表论文的发表时间）