Insights into Predicting Tooth Extraction from Panoramic Dental Images: Artificial Intelligence vs. Dentists.

Journal: Clinical oral investigations
PMID:

Abstract

OBJECTIVES: Tooth extraction is one of the most frequently performed medical procedures. The indication is based on the combination of clinical and radiological examination and individual patient parameters and should be made with great care. However, determining whether a tooth should be extracted is not always a straightforward decision. Moreover, visual and cognitive pitfalls in the analysis of radiographs may lead to incorrect decisions. Artificial intelligence (AI) could be used as a decision support tool to provide a score of tooth extractability.

Authors

  • Ila Motmaen
    Department of Oral and Maxillofacial Surgery, University Hospital Knappschaftskrankenhaus Bochum, 44892, Bochum, Germany.
  • Kunpeng Xie
    Department of Oral and Maxillofacial Surgery, University Hospital RWTH Aachen, Pauwelsstr. 30, 52074 Aachen, Germany; Institute of Medical Informatics, University Hospital RWTH Aachen, Pauwelsstr. 30, 52074 Aachen, Germany; Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD), Pauwelsstraße 30, 52074 Aachen, Germany.
  • Leon Schönbrunn
    Department of Oral and Maxillofacial Surgery, University Hospital RWTH Aachen, Pauwelsstraße 30, 52074, Aachen, Germany.
  • Jeff Berens
    Department of Oral and Maxillofacial Surgery, University Hospital RWTH Aachen, Pauwelsstraße 30, 52074, Aachen, Germany.
  • Kim Grunert
    Department of Oral and Maxillofacial Surgery, University Hospital RWTH Aachen, Pauwelsstraße 30, 52074, Aachen, Germany.
  • Anna Maria Plum
    Department of Oral and Maxillofacial Surgery, University Hospital RWTH Aachen, Pauwelsstraße 30, 52074, Aachen, Germany.
  • Johannes Raufeisen
    Department of Oral and Maxillofacial Surgery, University Hospital RWTH Aachen, Pauwelsstr. 30, 52074 Aachen, Germany; Institute of Medical Informatics, University Hospital RWTH Aachen, Pauwelsstr. 30, 52074 Aachen, Germany; Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD), Pauwelsstraße 30, 52074 Aachen, Germany.
  • André Ferreira
    Department of Oral and Maxillofacial Surgery, University Hospital RWTH Aachen, Pauwelsstraße 30, 52074, Aachen, Germany.
  • Alexander Hermans
    Visual Computing Institute (Computer Vision), RWTH Aachen University, Mies-van-der-Rohe Str. 15, 52074 Aachen, Germany.
  • Jan Egger
    Institute for Computer Graphics and Vision, Faculty of Computer Science and Biomedical Engineering, Graz University of Technology, Graz, Austria.
  • Frank Hölzle
    Department of Oral and Maxillofacial Surgery, RWTH Aachen University Hospital, Aachen, Germany.
  • Daniel Truhn
    Department of Diagnostic and Interventional Radiology, University Hospital Düsseldorf, Düsseldorf, Germany (J.S., D.B.A., S.N.); Institute of Computer Vision and Imaging, RWTH University Aachen, Pauwelsstrasse 30, 52072 Aachen, Germany (J.S., D.M.); Department of Diagnostic and Interventional Radiology, University Hospital Aachen, Aachen, Germany (D.T., M.P., F.M., C.K., S.N.); and Faculty of Mathematics and Natural Sciences, Institute of Informatics, Heinrich Heine University Düsseldorf, Düsseldorf, Germany (S.C.).
  • Behrus Puladi
    Institute of Medical Informatics, University Hospital RWTH Aachen, Pauwelsstraße 30, 52074 Aachen, Germany; Department of Oral and Maxillofacial Surgery, University Hospital RWTH Aachen, Pauwelsstraße 30, 52074 Aachen, Germany.