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An iterative Bayes algorithm for emission tomography using a smoothed sinogram

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1 Author(s)
Jun Ma ; Dept. of Stat., Macquarie Univ., North Ryde, NSW

In this paper we formulate a new approach to medical image reconstruction from projections in emission tomography. This approach differs from traditional methods such as filtered back projection, maximum likelihood or maximum penalized likelihood. Our method is developed directly from the Bayes formula and the final result is an iterative algorithm, for which the maximum likelihood expectation-maximization is a special case

Published in:

Biomedical Imaging: Nano to Macro, 2006. 3rd IEEE International Symposium on

Date of Conference:

6-9 April 2006