title: [Scatter correction of PET based on non-linear statistical estimate method].
abstract: Scatter coincident events are the important factor that affects the quality of positron emission tomography (PET) images. In this paper, according to the characters of projection data, a scatter correction method which uses maximum likelihood expectation maximization (MLEM) algorithm based on poisson model is proposed. We compared the sinograms and reconstructed images corrected by MLEM algorithm and deconvolution method respectively. The results indicate that the algorithm proposed in this paper increases the contrast of images while correcting scatter. It is better than the traditional method.
authors.affiliation: Department of Engineering Physics, Tsinghua University, Beijing, 100084, China. zxwu@mail.tsinghua.edu.cn
authors.forename: Zhaoxia
authors.initials: Z
authors.lastname: Wu
authors.forename: Shaoqing
authors.initials: S
authors.lastname: Chen
authors.forename: Jingzhi
authors.initials: J
authors.lastname: Cheng
mesh_terms: D000465:Algorithms; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D017711:Nonlinear Dynamics; D016012:Poisson Distribution; D049268:Positron-Emission Tomography / Q000379:methods*; D012542:Scattering, Radiation