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A parallel implementation of the maximum likelihood method in positron emission tomography image reconstruction

✍ Scribed by H. Jones; G. Mitra; D. Parkinson; T. Spinks

Publisher: Elsevier Science
Year: 1999
Tongue: English
Weight: 277 KB
Volume: 31
Category: Article
ISSN: 0167-9473
DOI: 10.1016/s0167-9473(99)00040-7

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✦ Synopsis

Positron emission tomography (PET) is a diagnostic technique that involves the reconstruction and quantiÿcation of the distribution of radioactivity within a body. Analytical reconstructions are relatively quick but statistical models yield possibly better reconstructions at the price of long computation times. We can, however, speed up the statistical techniques using parallel algorithms. This paper describes the implementation of a maximum likelihood (ML) method on a 12-processor Parsytec system.

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