Application of Regularized Least-squares Algorithm in PET Image Reconstruction Via a new Anisotropic Diffusion

摘要：

The traditional iterative reconstruction algorithms of positron emission tomography cannot effectively suppress the noise. In order to solve the problem, a new anisotropic diffusion term are introduced into the least-squares algorithm, and with median filter the regularized least-squares algorithm in PET image reconstruction based on anisotropic diffusion come into being. Results of computer simulated demonstrate that compared with the other classical reconstruction algorithms, LSNewAD not only availably suppress the noise and reconstruct a higher quality image, but also Effectively retains the edge of the image edge structure.

关键词： positron emission tomography anisotropic diffusion regularized least-squares

作者: Hu Yang Jiawei He Zhiguo Gui lina Yu

作者单位: National Key Laboratory For Electronic Measurement Technology ,North University of China,Taiyuan 030051, China

会议类型: 国际会议

会议名称: 2011 International Conference on Electronics and Optoelectronics(2011电子学与光电子学国际会议 ICEOE 2011)

会议地点: 大连

会议语种:英文

页码: 770-774

在线出版日期: 2011-07-29（万方平台首次上网日期，不代表论文的发表时间）