Detecting caries lesions of different radiographic extension on bitewings using deep learning.

Journal: Journal of dentistry
PMID: 32634466

Abstract

OBJECTIVES: We aimed to apply deep learning to detect caries lesions of different radiographic extension on bitewings, hypothesizing it to be significantly more accurate than individual dentists.

Authors

  • Anselmo Garcia Cantu
    Department of Oral Diagnostics, Digital Health and Health Services Research, Charité - Universitätsmedizin Berlin, Germany.
  • Sascha Gehrung
    Department of Oral Diagnostics, Digital Health and Health Services Research, Charité - Universitätsmedizin Berlin, Germany.
  • Joachim Krois
    Department of Operative and Preventive Dentistry, Charité - Universitätsmedizin Berlin, Berlin, Germany.
  • Akhilanand Chaurasia
    Department of Oral Medicine and Radiology, King George's Medical University, Lucknow, India.
  • Jesus Gomez Rossi
    Department of Oral Diagnostics, Digital Health and Health Services Research, Charité - Universitätsmedizin Berlin, Germany.
  • Robert Gaudin
    Department of Oral- and Maxillofacial Surgery, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Germany.
  • Karim Elhennawy
    Department of Operative and Preventive Dentistry, Charité-Universitätsmedizin Berlin, Berlin, Germany.
  • Falk Schwendicke
    Department of Operative and Preventive Dentistry, Charité - Universitätsmedizin Berlin, Berlin, Germany. falk.schwendicke@charite.de.

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