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25 May 1989 A Bayesian Reconstruction Algorithm for Emission Tomography using a Markov Random Field Prior
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Abstract
A Bayesian generalized expectation - maximization (GEM) algorithm using a locally correlated Markov random field prior in the form of a Gibbs function is developed for emission tomography. A close-form coordinate gradient ascent M-step which updates the image pixels sequentially is derived. The resulting GEM Bayesian algorithm is applied to estimating the 3-D image parameters in the Poisson model of emission sources based upon simulation of a parallel collimated gamma camera.
© (1989) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tom Hebert and Richard Leahy "A Bayesian Reconstruction Algorithm for Emission Tomography using a Markov Random Field Prior", Proc. SPIE 1092, Medical Imaging III: Image Processing, (25 May 1989); https://doi.org/10.1117/12.953287
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