Abstract
The image space reconstruction algorithm (ISRA) was proposed as a modification of the expectation maximization (EM) algorithm based on physical considerations for application in volume emission computered tomography. As a consequence of this modification, ISRA searches for least squares solutions instead of maximizing Poisson likelihoods as the EM algorithm. It is shown that both algorithms may be obtained from a common mathematical framework. This fact is used to extend ISRA for penalized likelihood estimates.

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