An iterative Bayes algorithm for emission tomography using a smoothed sinogram | Macquarie University ResearchOnline

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Title: An iterative Bayes algorithm for emission tomography using a smoothed sinogram
Related: 2006 IEEE International Symposium on Biomedical Imaging: From Nano to Macro (6 - 9 April, 2006 : Arlington, Virginia)
Related: IEEE International Symposium on Biomedical Imaging: Macro to Nano, 3rd, 2006
DOI: 10.1109/ISBI.2006.1625142
Publisher: Piscataway, USA : IEEE
Date: 2006
Author/Creator: Ma, Jun
Description: 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.
Description: 4 page(s)
Subject Keyword: Bayes method
Subject Keyword: expectation-maximisation algorithm
Subject Keyword: image reconstruction
Subject Keyword: medical image processing
Resource Type: conference paper
Organisation: Macquarie University. Dept. of Statistics

Identifier: http://hdl.handle.net/1959.14/16356
Identifier: ISBN:078039576X
Identifier: mq-rm-2006002217
Language: eng
Rights: Copyright 2006 IEEE. Reprinted from IEEE International Symposium on Biomedical Imaging: Macro to Nano, 3rd, 2006. 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 pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
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