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dc.contributor.authorNúñez de Murga, Jorge, 1955-cat
dc.contributor.authorLlacer, Jorgecat
dc.description.abstractThe development and tests of an iterative reconstruction algorithm for emission tomography based on Bayesian statistical concepts are described. The algorithm uses the entropy of the generated image as a prior distribution, can be accelerated by the choice of an exponent, and converges uniformly to feasible images by the choice of one adjustable parameter. A feasible image has been defined as one that is consistent with the initial data (i.e. it is an image that, if truly a source of radiation in a patient, could have generated the initial data by the Poisson process that governs radioactive disintegration). The fundamental ideas of Bayesian reconstruction are discussed, along with the use of an entropy prior with an adjustable contrast parameter, the use of likelihood with data increment parameters as conditional probability, and the development of the new fast maximum a posteriori with entropy (FMAPE) Algorithm by the successive substitution method. It is shown that in the maximum likelihood estimator (MLE) and FMAPE algorithms, the only correct choice of initial image for the iterative procedure in the absence of a priori knowledge about the image configuration is a uniform field.eng
dc.relation.isformatofReproducció del document publicat a
dc.relation.ispartofIEEE Transactions on Medical Imaging, 1990, vol. 9, núm. 2, p.
dc.rights(c) IEEE, 1990cat
dc.sourceArticles publicats en revistes (Física Quàntica i Astrofísica)-
dc.subject.classificationEstadística bayesianacat
dc.subject.classificationTomografia d'emissiócat
dc.subject.otherBayes methodseng
dc.subject.otherComputerised tomographyeng
dc.subject.otherRadioisotope scanning and imagingeng
dc.titleA fast Bayesian reconstruction algorithm for emission tomography with entropy prior converging to feasible imageseng
Appears in Collections:Articles publicats en revistes (Física Quàntica i Astrofísica)

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