CT metal artefact reduction for hip and shoulder implants using novel algorithms and machine learning: A systematic review with pairwise and network meta-analyses.

Journal: Radiography (London, England : 1995)
PMID: 39509906

Abstract

INTRODUCTION: Many tools have been developed to reduce metal artefacts in computed tomography (CT) images resulting from metallic prosthesis; however, their relative effectiveness in preserving image quality is poorly understood. This paper reviews the literature on novel metal artefact reduction (MAR) methods targeting large metal artefacts in fan-beam CT to examine their effectiveness in reducing metal artefacts and effect on image quality.

Authors

  • K Amadita
    Discipline of Medical Imaging Science, Faculty of Medicine and Health, University of Sydney, NSW 2006, Australia. Electronic address: katya.amadita@sydney.edu.au.
  • F Gray
    Discipline of Medical Imaging Science, Faculty of Medicine and Health, University of Sydney, NSW 2006, Australia. Electronic address: frances.gray@sydney.edu.au.
  • E Gee
    Discipline of Medical Imaging Science, Faculty of Medicine and Health, University of Sydney, NSW 2006, Australia. Electronic address: erin.gee@sydney.edu.au.
  • E Ekpo
    Discipline of Medical Imaging Science, Faculty of Medicine and Health, University of Sydney, NSW 2006, Australia. Electronic address: ernest.ekpo@sydney.edu.au.
  • Y Jimenez
    Discipline of Medical Imaging Science, Faculty of Medicine and Health, University of Sydney, NSW 2006, Australia. Electronic address: yobelli.jimenez@sydney.edu.au.

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