String-averaging expectation-maximization for maximum likelihood estimation in emission tomography
Elias S. Helou,Yair Censor,Tai-Been Chen,I-Liang Chern,I-Liang Chern,Alvaro R. De Pierro,Ming Jiang,Henry Horng Shing Lu +7 more
TL;DR: Study of the maximum likelihood model in emission tomography and a new family of algorithms for its solution, called string-averaging expectationmaximization (SAEM), which present better practical merits than the classical row-action maximum-likelihood algorithm.
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Abstract: We study the maximum likelihood model in emission tomography and propose a new family of algorithms for its solution, called string-averaging expectationmaximization (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
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Citations
Parallel Optimization: Theory, Algorithms and Applications
TL;DR: Yair Censor and Stavros A. Zenios, Oxford University Press, New York, 1997, 539 pp.
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