Abstract
In this paper we formulate a new approach to medical image reconstruction from projections in emission tomography. This approach conceptually differs from the traditional methods such as filtered backprojection, maximum likelihood or maximum penalized likelihood. Similar to the Richardson-Lucy algorithm ([1], [2]), our method develops directly from the Bayes formula with the final result being an iterative algorithm, for which the maximum likelihood expectation-maximization of [3] (or [4]) is a special case. Although there are different ways to enforce smoothness in the reconstructions using this method, in this paper we opt to focus only on the way which smoothes the camera bin measurements before reconstruction. In fact, this method can be explicated as maximizing a special penalized log-likelihood function. Its theoretical properties are also analyzed in the paper.
Original language | English |
---|---|
Article number | 4545158 |
Pages (from-to) | 953-966 |
Number of pages | 14 |
Journal | IEEE Transactions on Nuclear Science |
Volume | 55 |
Issue number | 3 |
DOIs | |
Publication status | Published - Jun 2008 |
Bibliographical note
Copyright 2008 IEEE. Reprinted from IEEE transactions on nuclear science. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Macquarie University’s products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.Keywords
- EM
- Iterative Bayes algorithm
- MPL
- Smoothed sinogram