String-averaging expectation-maximization for maximum likelihood estimation in emission tomography

dc.contributorUniversidade Estadual Paulista (UNESP)
dc.creatorHelou, Elias Salomao
dc.creatorCensor, Yair
dc.creatorChen, Tai-Been
dc.creatorChern, I-Liang
dc.creatorDe Pierro, Alvaro Rodolfo
dc.creatorJiang, Ming
dc.creatorLu, Henry Horng-Shing
dc.date2014-12-03T13:09:00Z
dc.date2016-10-25T20:09:48Z
dc.date2014-12-03T13:09:00Z
dc.date2016-10-25T20:09:48Z
dc.date2014-05-01
dc.date.accessioned2017-04-06T06:16:41Z
dc.date.available2017-04-06T06:16:41Z
dc.identifierInverse Problems. Bristol: Iop Publishing Ltd, v. 30, n. 5, 20 p., 2014.
dc.identifier0266-5611
dc.identifierhttp://hdl.handle.net/11449/111820
dc.identifierhttp://acervodigital.unesp.br/handle/11449/111820
dc.identifier10.1088/0266-5611/30/5/055003
dc.identifierWOS:000336265400003
dc.identifierhttp://dx.doi.org/10.1088/0266-5611/30/5/055003
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/922593
dc.descriptionWe 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.
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.languageeng
dc.publisherIop Publishing Ltd
dc.relationInverse Problems
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectpositron emission tomography (PET)
dc.subjectstring-averaging
dc.subjectblock-iterative
dc.subjectexpectation-maximization (EM) algorithm
dc.subjectordered subsets expectation maximization (OSEM) algorithm
dc.subjectrelaxed EM
dc.subjectstring-averaging EM algorithm
dc.titleString-averaging expectation-maximization for maximum likelihood estimation in emission tomography
dc.typeOtro


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