Evaluation of a deep learning system for automatic detection of proximal surface dental caries on bitewing radiographs.

Journal: Oral surgery, oral medicine, oral pathology and oral radiology
Published Date: Mar 18, 2022

Abstract

OBJECTIVE: This study aimed to evaluate a deep learning (DL) system using convolutional neural networks (CNNs) for automatic detection of caries on bitewing radiographs.

Authors

  • Mohamed Estai
    The Australian e-Health Research Centre, CSIRO, Floreat, Australia.
  • Marc Tennant
    School of Human Sciences, The University of Western Australia, Crawley, Australia.
  • Dieter Gebauer
    School of Human Sciences, The University of Western Australia, Crawley, Australia.
  • Andrew Brostek
    The UWA Dental School, The University of Western Australia, Crawley, Australia.
  • Janardhan Vignarajan
    Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation, Perth, Western Australia, Australia.
  • Maryam Mehdizadeh
    The Australian e-Health Research Centre, CSIRO, Floreat, Australia.
  • Sajib Saha
    Doheny Eye Institute, Los Angeles, CA, 90033, USA.

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