標題: String-averaging expectation-maximization for maximum likelihood estimation in emission tomography
作者: Helou, Elias Salomao
Censor, Yair
Chen, Tai-Been
Chern, I-Liang
De Pierro, Alvaro Rodolfo
Jiang, Ming
Lu, Henry Horng-Shing
數學建模與科學計算所(含中心)
統計學研究所
Graduate Program of Mathematical Modeling and Scientific Computing, Department of Applied Mathematics
Institute of Statistics
關鍵字: positron emission tomography (PET);string-averaging;block-iterative;expectation-maximization (EM) algorithm;ordered subsets expectation maximization (OSEM) algorithm;relaxed EM;string-averaging EM algorithm
公開日期: 1-五月-2014
摘要: We study the maximum likelihood model in emission tomography and propose a new family of algorithms for its solution, called string-averaging expectation maximization (SAEM). In the string-averaging algorithmic regime, the index set of all underlying equations is split into subsets, called \'strings\', and the algorithm separately proceeds along each string, possibly in parallel. Then, the end-points of all strings are averaged to form the next iterate. SAEM algorithms with several strings present better practical merits than the classical row-action maximum-likelihood algorithm. We present numerical experiments showing the effectiveness of the algorithmic scheme, using data of image reconstruction problems. Performance is evaluated from the computational cost and reconstruction quality viewpoints. A complete convergence theory is also provided.
URI: http://dx.doi.org/10.1088/0266-5611/30/5/055003
http://hdl.handle.net/11536/24445
ISSN: 0266-5611
DOI: 10.1088/0266-5611/30/5/055003
期刊: INVERSE PROBLEMS
Volume: 30
Issue: 5
結束頁: 
顯示於類別:期刊論文


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  1. 000336265400003.pdf