An iterative Bayes algorithm for emission tomography using a smoothed sinogram

Jun Ma*

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

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    Abstract

    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 of [1] (or [2]) is a special case.

    Original languageEnglish
    Title of host publication2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings
    Place of PublicationPiscataway, N.J
    PublisherInstitute of Electrical and Electronics Engineers (IEEE)
    Pages1212-1215
    Number of pages4
    Volume2006
    ISBN (Print)0780395778, 9780780395770
    Publication statusPublished - 2006
    Event2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Arlington, VA, United States
    Duration: 6 Apr 20069 Apr 2006

    Other

    Other2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro
    CountryUnited States
    CityArlington, VA
    Period6/04/069/04/06

    Bibliographical note

    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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