Deep Learning for Predicting the Difficulty Level of Removing the Impacted Mandibular Third Molar.

Journal: International dental journal
PMID: 39043529

Abstract

BACKGROUND: Preoperative assessment of the impacted mandibular third molar (LM3) in a panoramic radiograph is important in surgical planning. The aim of this study was to develop and evaluate a computer-aided visualisation-based deep learning (DL) system using a panoramic radiograph to predict the difficulty level of surgical removal of an impacted LM3.

Authors

  • Vorapat Trachoo
    Faculty of Dentistry, Chulalongkorn University, Bangkok, Thailand.
  • Unchalisa Taetragool
    Department of Computer Engineering, King Mongkut's University of Technology Thonburi, Bangkok, 10140, Thailand.
  • Ploypapas Pianchoopat
    Department of Computer Engineering, Faculty of Engineering, King Mongkut's University of Technology Thonburi, Bangkok, Thailand.
  • Chatchapon Sukitporn-Udom
    Department of Computer Engineering, Faculty of Engineering, King Mongkut's University of Technology Thonburi, Bangkok, Thailand.
  • Narapathra Morakrant
    Department of Computer Engineering, Faculty of Engineering, King Mongkut's University of Technology Thonburi, Bangkok, Thailand.
  • Kritsasith Warin
    Division of Oral and Maxillofacial Surgery, Faculty of Dentistry, Thammasat University, Pathum Thani, Thailand.

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