Artificial Intelligence for Root Canal Orifice Identification Using Dental Operating Microscope Images: A Preliminary Evaluation

KARATAŞ E., Ünal O., ÇELİK Ö., BAYRAKDAR İ. Ş.

Australian Endodontic Journal, 2025 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Publication Date: 2025
  • Doi Number: 10.1111/aej.12955
  • Journal Name: Australian Endodontic Journal
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, EMBASE, MEDLINE
  • Keywords: artificial intelligence (AI), deep learning, dental operating microscope (DOM), endodontics, orifice detection, root canal orifice, YOLO model
  • Eskisehir Osmangazi University Affiliated: Yes

Abstract

To evaluate the diagnostic performance of artificial intelligence (AI) in detecting root canal orifices using images captured with a dental operating microscope (DOM). A total of 80 human maxillary first and second molars were included in the study. After preparing traditional access cavities, root canal orifices were identified under a dental operating microscope (DOM) at 21.25× magnification. Following orifice identification, video recordings were obtained using the DOM, from which a total of 1527 frames were randomly selected for analysis. The root canal orifices in these frames were manually labelled using CranioCatch labeling software (CranioCatch, Eskişehir, Turkey). In the binary classification task, the system correctly identified 502 out of 526 root canal orifices, yielding an accuracy of 91%. The YOLO-based CNN demonstrated high accuracy and sensitivity in detecting root canal orifices from DOM images.