Abstract

A three-dimensional maximum-likelihood reconstruction method is presented for a prototype electronically collimated single-photon-emission system. The electronically collimated system uses a gamma camera fronted by an array of germanium detectors to detect gamma-ray emissions from a distributed radioisotope source. In this paper we demonstrate that optimal iterative three-dimensional reconstruction approaches can be feasibly applied to emission imaging systems that have highly complex spatial sampling patterns and that generate extremely large numbers of data values. A probabilistic factorization of the system matrix that reduces the computation by several orders of magnitude is derived. We demonstrate a dramatic increase in the convergence speed of the expectation maximization algorithm by sequentially iterating over particular subsets of the data. This result is also applicable to other emission imaging systems.

© 1990 Optical Society of America

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