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A modified expectation maximization algorithm for penalized likelihood estimation in emission tomography
472
Zitationen
1
Autoren
1995
Jahr
Abstract
The maximum likelihood (ML) expectation maximization (EM) approach in emission tomography has been very popular in medical imaging for several years. In spite of this, no satisfactory convergent modifications have been proposed for the regularized approach. Here, a modification of the EM algorithm is presented. The new method is a natural extension of the EM for maximizing likelihood with concave priors. Convergence proofs are given.
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