Multi-modal deep learning for automated assembly of periapical radiographs.

Journal: Journal of dentistry
Published Date: Jun 21, 2023

Abstract

OBJECTIVES: Periapical radiographs are oftentimes taken in series to display all teeth present in the oral cavity. Our aim was to automatically assemble such a series of periapical radiographs into an anatomically correct status using a multi-modal deep learning model.

Authors

  • L Pfänder
    Department of Oral Diagnostics, Digital Health and Health Services Research, Charité-Universitätsmedizin Berlin, 14197 Berlin, Germany.
  • L Schneider
    Department of Oral Diagnostics, Digital Health and Health Services Research, Charité-Universitätsmedizin, Berlin, Germany.
  • M Büttner
    Department of Oral Diagnostics, Digital Health and Health Services Research, Charité-Universitätsmedizin Berlin, 14197 Berlin, Germany; ITU/WHO Focus Group AI4Health, Topic Group Dental Diagnostics and Digital Dentistry, Geneva, Switzerland.
  • J Krois
    Department of Operative and Preventive Dentistry, Charité - Universitätsmedizin Berlin, Berlin, Germany.
  • H Meyer-Lueckel
    Department of Restorative, Preventive and Pediatric Dentistry, Zahnmedizinische Kliniken der Universität Bern, University of Bern, Bern, Switzerland.
  • F Schwendicke
    Department of Operative and Preventive Dentistry, Charité - Universitätsmedizin Berlin, Berlin, Germany.

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