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

dc.contributorUniversidade Estadual Paulista (Unesp)
dc.contributorUniv Haifa
dc.contributorI Shou Univ
dc.contributorNatl Chiao Tung Univ
dc.contributorNatl Taiwan Univ
dc.contributorPeking Univ
dc.creatorHelou, Elias Salomao [UNESP]
dc.creatorCensor, Yair
dc.creatorChen, Tai-Been
dc.creatorChern, I-Liang
dc.creatorDe Pierro, Alvaro Rodolfo [UNESP]
dc.creatorJiang, Ming
dc.creatorLu, Henry Horng-Shing
dc.date2014-12-03T13:09:00Z
dc.date2014-12-03T13:09:00Z
dc.date2014-05-01
dc.date.accessioned2023-09-09T09:49:35Z
dc.date.available2023-09-09T09:49:35Z
dc.identifierhttp://dx.doi.org/10.1088/0266-5611/30/5/055003
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.identifier10.1088/0266-5611/30/5/055003
dc.identifierWOS:000336265400003
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8761479
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.descriptionUnited States-Israel Binational Science Foundation (BSF)
dc.descriptionUS Department of Army award
dc.descriptionNational Science Council of the Republic of China, Taiwan
dc.descriptionNational Center for Theoretical Sciences (Taipei Office)
dc.descriptionNational Science Council of the Republic of China
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionNational Basic Research and Development Program of China (973 Program)
dc.descriptionNational Science Foundation of China
dc.descriptionNational Science Council
dc.descriptionNational Center for Theoretical Sciences
dc.descriptionCenter of Mathematical Modeling and Scientific Computing at National Chiao Tung University in Taiwan
dc.descriptionState Univ Sao Paulo, Dept Appl Math & Stat, Sao Carlos, SP, Brazil
dc.descriptionUniv Haifa, Dept Math, IL-3190501 Haifa, Israel
dc.descriptionI Shou Univ, Dept Med Imaging & Radiol Sci, Kaohsiung 82445, Taiwan
dc.descriptionNatl Chiao Tung Univ, Ctr Math Modeling & Sci Comp, Dept Appl Math, Hsinchu 30010, Taiwan
dc.descriptionNatl Taiwan Univ, Dept Math, Taipei 10617, Taiwan
dc.descriptionPeking Univ, Beijing Int Ctr Math Res, Sch Math Sci, LMAM, Beijing 100871, Peoples R China
dc.descriptionNatl Chiao Tung Univ, Inst Stat, Hsinchu 30010, Taiwan
dc.descriptionState Univ Sao Paulo, Dept Appl Math & Stat, Sao Carlos, SP, Brazil
dc.descriptionFAPESP: 13/16508-3
dc.descriptionUnited States-Israel Binational Science Foundation (BSF)200912
dc.descriptionUS Department of Army awardW81XWH-10-1-0170
dc.descriptionNational Science Council of the Republic of China, TaiwanNSC 97-2118-M-214-001-MY2
dc.descriptionNational Science Council of the Republic of ChinaNSC 99-2115-M-002-003-MY3
dc.descriptionCNPq: 301064/2009-1
dc.descriptionNational Basic Research and Development Program of China (973 Program)2011CB809105
dc.descriptionNational Science Foundation of China61121002
dc.descriptionNational Science Foundation of China10990013
dc.descriptionNational Science Foundation of China60325101
dc.format20
dc.languageeng
dc.publisherIop Publishing Ltd
dc.relationInverse Problems
dc.relation1.946
dc.relation1,209
dc.rightsAcesso restrito
dc.sourceWeb of Science
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.typeArtigo


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