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• W2044656938 abstract "The expectation maximization method for maximum likelihood image reconstruction in emission tomography, based on the Poisson distribution of the statistically independent components of the image and measurement vectors, is extended to a maximum aposteriori image reconstruction using a multivariate Gaussian a priori probability distribution of the image vector. The approach is equivalent to a penalized maximum likelihood estimation with a special choice of the penalty function. The expectation maximization method is applied to find the a posteriori probability maximizer. A simple iterative formula is derived for a penalty function that is a weighted sum of the squared deviations of image vector components from their a priori mean values. The method is demonstrated to be superior to pure likelihood maximization, in that the penalty function prevents the occurrence of irregular high amplitude patterns in the image with a large number of iterations (the so-called checkerboard effect or noise artifact)." @default.
• W2044656938 created "2016-06-24" @default.
• W2044656938 creator A5030577876 @default.
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• W2044656938 date "1987-09-01" @default.
• W2044656938 modified "2023-10-14" @default.
• W2044656938 title "A Maximum a Posteriori Probability Expectation Maximization Algorithm for Image Reconstruction in Emission Tomography" @default.
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• W2044656938 doi "https://doi.org/10.1109/tmi.1987.4307826" @default.
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