[Scatter correction of PET based on non-linear statistical estimate method].

Zhaoxia Wu; Shaoqing Chen; Jingzhi Cheng

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PubMed · 15762120

[Scatter correction of PET based on non-linear statistical estimate method].

Zhaoxia Wu·Shaoqing Chen·Jingzhi Cheng

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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.

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Algorithms Image Processing, Computer-Assisted Nonlinear Dynamics Poisson Distribution Positron-Emission Tomography Scattering, Radiation English Abstract Journal Article

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BibTeX RIS

Zhaoxia Wu, Shaoqing Chen, Jingzhi Cheng. 2005. [Scatter correction of PET based on non-linear statistical estimate method].. https://pubmed.ncbi.nlm.nih.gov/15762120/

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