Automated detection of posterior restorations in permanent teeth using artificial intelligence on intraoral photographs.

Journal: Journal of dentistry
PMID: 35395346

Abstract

OBJECTIVES: Intraoral photographs might be considered the machine-readable equivalent of a clinical-based visual examination and can potentially be used to detect and categorize dental restorations. The first objective of this study was to develop a deep learning-based convolutional neural network (CNN) for automated detection and categorization of posterior composite, cement, amalgam, gold and ceramic restorations on clinical photographs. Second, this study aimed to determine the diagnostic accuracy for the developed CNN (test method) compared to that of an expert evaluation (reference standard).

Authors

  • Paula Engels
    Department of Conservative Dentistry and Periodontology, University Hospital, Ludwig-Maximilians University Munich, Goethestraße 70, Munich 80336, Germany.
  • Ole Meyer
    Institute for Software Engineering, University of Duisburg-Essen, Essen, Germany.
  • Jule Schönewolf
    Department of Conservative Dentistry and Periodontology, University Hospital, Ludwig-Maximilians University Munich, Goethestraße 70, Munich 80336, Germany.
  • Anne Schlickenrieder
    Department of Conservative Dentistry and Periodontology, University Hospital, Ludwig-Maximilians University Munich, Goethestraße 70, Munich 80336, Germany.
  • Reinhard Hickel
    Department of Conservative Dentistry and Periodontology, University Hospital, Ludwig-Maximilians University Munich, Goethestraße 70, Munich 80336, Germany.
  • Marc Hesenius
    Institute for Software Engineering, University of Duisburg-Essen, Essen, Germany.
  • Volker Gruhn
    Institute for Software Engineering, University of Duisburg-Essen, Essen, Germany.
  • Jan Kühnisch
    Department of Conservative Dentistry and Periodontology, University Hospital, Ludwig-Maximilians University Munich, Goethestraße 70, Munich 80336, Germany. Electronic address: jkuehn@dent.med.uni-muenchen.de.

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