{"title":"Hidden-data spaces for maximum-likelihood PET reconstruction","authors":"J. Fessler","doi":"10.1109/NSSMIC.1992.301014","DOIUrl":null,"url":null,"abstract":"The author shows that expectation-maximization (EM) algorithms based on smaller complete data spaces will typically converge faster. As an example, he compares the two maximum-likelihood (ML) image reconstruction algorithms of D. G. Politte and D. L. Snyder (1991) which are based on measurement models that account for attenuation and accidental coincidences in positron-emission tomography (PET).<<ETX>>","PeriodicalId":447239,"journal":{"name":"IEEE Conference on Nuclear Science Symposium and Medical Imaging","volume":"92 7","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Conference on Nuclear Science Symposium and Medical Imaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NSSMIC.1992.301014","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The author shows that expectation-maximization (EM) algorithms based on smaller complete data spaces will typically converge faster. As an example, he compares the two maximum-likelihood (ML) image reconstruction algorithms of D. G. Politte and D. L. Snyder (1991) which are based on measurement models that account for attenuation and accidental coincidences in positron-emission tomography (PET).<>
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