A two-stage deep-learning model for determination of the contact of mandibular third molars with the mandibular canal on panoramic radiographs.

Journal: BMC oral health
PMID:

Abstract

OBJECTIVES: This study aimed to assess the accuracy of a two-stage deep learning (DL) model for (1) detecting mandibular third molars (MTMs) and the mandibular canal (MC), and (2) classifying the anatomical relationship between these structures (contact/no contact) on panoramic radiographs.

Authors

  • Parisa Soltani
    Department of Oral and Maxillofacial Radiology, Dental Implants Research Center, Dental Research Institute, School of Dentistry, Isfahan University of Medical Sciences, Salamat Blv, Isfahan Dental School, Isfahan, Iran.
  • Fatemeh Sohrabniya
    Topic Group Dental Diagnostics and Digital Dentistry, ITU/WHO Focus Group AI on Health, Berlin, Germany.
  • Hossein Mohammad-Rahimi
    Division of Artificial Intelligence Imaging Research, University of Maryland School of Dentistry, Baltimore, MD 21201, USA.
  • Mojdeh Mehdizadeh
    Department of Oral and Maxillofacial Radiology, Dental Implants Research Center, Dental Research Institute, School of Dentistry, Isfahan University of Medical Sciences, Isfahan, Iran.
  • Seyed Mohammadreza Mousavi
    Students Research Committee, School of Dentistry, Isfahan University of Medical Sciences, Isfahan, Iran.
  • Amirhossein Moaddabi
    Department of Oral and Maxillofacial Surgery, Dental Research Center, Mazandaran University of Medical Sciences, Sari, Iran. a.moaddabi@mazums.ac.ir.
  • Seyed Mohammadmahdi Mousavi
    School of Dentistry, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
  • Gianrico Spagnuolo
    Department of Neurosciences, Reproductive and Odontostomatological Sciences, Università di Napoli Federico II, via S. Pansini, 5-80131 Naples, Italy.
  • Amirmohammad Yavari
    Student Research Committee, School of Dentistry, Isfahan University of Medical Sciences, Isfahan, Iran.
  • Falk Schwendicke
    Department of Operative and Preventive Dentistry, Charité - Universitätsmedizin Berlin, Berlin, Germany. falk.schwendicke@charite.de.