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

Authors

  • S Ozudogru Department of Pediatric Dentistry, Faculty of Dentistry, Istanbul Medeniyet University, Istanbul
  • E Gulsen Alanya Oral and Dental Health Center, Antalya, Turkey - *** Department of Pediatric Dentistry, Faculty of Dentistry, Inonu University, Malatya
  • T Mahyaddinova Alanya Oral and Dental Health Center, Antalya, Turkey - *** Department of Pediatric Dentistry, Faculty of Dentistry, Inonu University, Malatya
  • FN Kizilay  
  • IT 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
  • A Kuran  
  • E Bilgir Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Eskisehir Osmangazi University, Eskişehir
  • AF Aslan Department of Mathematics-Computer, Eskisehir Osmangazi University Faculty of Science, Eskisehir
  • O Celik Department of Mathematics-Computer, Eskisehir Osmangazi University Faculty of Science, Eskisehir
  • IS Bayrakdar Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Eskisehir Osmangazi University, Eskişehir

DOI:

https://doi.org/10.23804/ejpd.2025.2292

Keywords:

Artificial intelligence, tooth detecting, CBCT, paediatric dentistry, mixed dentition

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. BACKGROUND: Identifying and numbering teeth, the initial step in treatment planning, demands an efficient method. CONCLUSION: AI models offer a promising approach in the mixed dentition period and play a valuable role in dentists' planning in terms of time and effort.

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