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Related Experiment Videos

List-mode likelihood

H H Barrett1, T White, L C Parra

  • 1Department of Radiology and Optical Sciences Center, University of Arizona, Tucson, USA. barrett@radiology.arizona.edu

Journal of the Optical Society of America. A, Optics, Image Science, and Vision
|November 14, 1997
PubMed
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This study introduces likelihood expressions for list-mode data in photon-counting imaging. This approach efficiently handles complex imaging data with multiple attributes per event, improving data analysis.

Area of Science:

  • Medical Imaging
  • Photon-Counting Detectors
  • Data Acquisition

Background:

  • Photon-counting imaging systems are increasing in complexity, leading to the measurement of multiple event attributes.
  • Traditional image matrix formats are impractical for data with more than four attributes per event.
  • List-mode data storage, where all attributes are recorded for each event, offers a more efficient alternative.

Purpose of the Study:

  • To discuss the concept of likelihood for list-mode data in photon-counting imaging.
  • To present expressions for list-mode likelihood with an arbitrary number of attributes per photon.
  • To derive an expression for lesion detectability using list-mode data.

Main Methods:

  • Development of likelihood expressions for list-mode data accommodating multiple attributes per photon.

Related Experiment Videos

  • Formulation for both preset counts and preset time acquisition modes.
  • Derivation of a lesion detectability expression for list-mode data.

    • Main Results:

    • Established practical likelihood expressions for list-mode data in advanced photon-counting imaging.
    • Provided a framework for developing reconstruction algorithms from list-mode data.
    • Derived a quantitative measure for lesion detectability in list-mode datasets.

    Conclusions:

    • List-mode data offers a viable and efficient method for handling complex photon-counting imaging data.
    • The presented likelihood framework supports the development of advanced image reconstruction techniques.
    • The derived lesion detectability expression facilitates performance evaluation of list-mode imaging systems.