Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/8542
Title: A fast Bayesian reconstruction algorithm for emission tomography with entropy prior converging to feasible images
Author: Núñez de Murga, Jorge, 1955-
Llacer, Jorge
Keywords: Estadística bayesiana
Tomografia d'emissió
Entropia
Bayes methods
Computerised tomography
Entropy
Radioisotope scanning and imaging
Issue Date: 1990
Publisher: IEEE
Abstract: The 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.
Note: Reproducció del document publicat a http://dx.doi.org/10.1109/42.56340
It is part of: IEEE Transactions on Medical Imaging, 1990, vol. 9, núm. 2, p. 159-171.
URI: http://hdl.handle.net/2445/8542
ISSN: 0278-0062
Appears in Collections:Articles publicats en revistes (Física Quàntica i Astrofísica)

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