NOISE AND EDGE ARTIFACTS IN MAXIMUM-LIKELIHOOD RECONSTRUCTIONS FOR EMISSION TOMOGRAPHY

Images produced in emission tomography with the expectation-maximization algorithm have been observed to become more noisy and to have large distortions near edges as iterations proceed and the images converge towards the maximum-likelihood estimate. It is our conclusion that these artifacts are fundamental to reconstructions based on maximum-likelihood estimation as it has been applied usually; they are not due to the use of the expectation-maximization algorithm, which is but one numerical approach for finding the maxi-mum-likelihood estimate. In this paper, we develop a mathematical approach for suppressing both the noise and edge artifacts by modifying the maximum-likelihood approach to include constraints which the estimate must satisfy. Copyright © 1987 by The Institute of Electrical and Electronics Engineers, Inc.