Artificial intelligence system for automatic tooth detection and numbering in the mixed dentition in CBCT.

Journal: European journal of paediatric dentistry
Published Date: Feb 1, 2025

Abstract

AIM: To evaluate the effectiveness and accuracy of artificial intelligence (AI) by automating tooth segmentation in CBCT volumes of paediatric patients with mixed dentition, using nnU-Netv2 algorithm.

Authors

  • S Ozudogru
    Department of Pediatric Dentistry, Faculty of Dentistry, Istanbul Medeniyet University, Istanbul, Turkey.
  • E Gulsen
    Alanya Oral and Dental Health Center, Antalya, Turkey - *** Department of Pediatric Dentistry, Faculty of Dentistry, Inonu University.
  • T Mahyaddinova
    Alanya Oral and Dental Health Center, Antalya, Turkey - *** Department of Pediatric Dentistry, Faculty of Dentistry, Inonu University.
  • F N Kizilay
  • I T Gulsen
    Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Alanya Alaaddin Keykubat University, Antalya, Turkey - ***** Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Kocaeli University, Kocaeli, Turkey.
  • A Kuran
  • E Bilgir
    Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Eskisehir Osmangazi University, Eskişehir, Turkey.
  • A F Aslan
    Department of Mathematics-Computer, Eskisehir Osmangazi University Faculty of Science, Eskisehir, Turkey.
  • O Celik
    Department of Mathematics-Computer, Eskisehir Osmangazi University Faculty of Science, Eskisehir, Turkey.
  • I S Bayrakdar
    Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Eskisehir Osmangazi University, Eskişehir, Turkey.

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