A clinical perspective of accelerated statistical reconstruction

Brian F. Hutton*, H. Malcolm Hudson, Freek J. Beekman

*Corresponding author for this work

    Research output: Contribution to journalReview articlepeer-review

    102 Citations (Scopus)

    Abstract

    Although the potential benefits of maximum likelihood reconstruction have been recognised for many years, the technique has only recently found widespread popularity in clinical practice. Factors which have contributed to the wider acceptance include improved models for the emission process, better understanding of the properties of the algorithm and, not least, the practicality of application with the development of acceleration schemes and the improved speed of computers. The objective in this article is to present a framework for applying maximum likelihood reconstruction for a wide range of clinically based problems. The article draws particularly on the experience of the three authors in applying an acceleration scheme involving use of ordered subsets to a range of applications. The potential advantages of statistical reconstruction techniques include: (a) the ability to better model the emission and detection process, in order to make the reconstruction converge to a quantitative image, (b) the inclusion of a statistical noise model which results in better noise characteristics, and (c) the possibility to incorporate prior knowledge about the distribution being imaged. The great flexibility in adapting the reconstruction for a specific model results in these techniques having wide applicability to problems in clinical nuclear medicine.

    Original languageEnglish
    Pages (from-to)797-808
    Number of pages12
    JournalEuropean Journal of Nuclear Medicine
    Volume24
    Issue number7
    DOIs
    Publication statusPublished - 1997

    Keywords

    • Fast image processing
    • Maximum likelihood reconstruction
    • Single-photon emission tomography

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