Performance of a convolutional neural network algorithm for tooth detection and numbering on periapical radiographs.

Journal: Dento maxillo facial radiology
Published Date: Oct 8, 2021

Abstract

OBJECTIVES: The present study aimed to evaluate the performance of a Faster Region-based Convolutional Neural Network (R-CNN) algorithm for tooth detection and numbering on periapical images.

Authors

  • Cansu Görürgöz
    Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Bursa Uludağ University, Bursa, Turkey.
  • Kaan Orhan
    Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Dentomaxillofacial Radiologist, Ankara University, Ankara, Turkey.
  • İbrahim Şevki Bayrakdar
    Department of Oral Diagnosis and Radiology, Faculty of Dentistry, Eskişehir Osmangazi University, Eskişehir, Turkey.
  • Özer Çelik
    Department of Mathematics and Computer, Faculty of Science and Letters, Eskişehir Osmangazi University, Eskişehir, Turkey.
  • Elif Bilgir
    Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Eskisehir Osmangazi University, Eskisehir, Turkey.
  • Alper Odabaş
    Department of Mathematics and Computer Science, Faculty of Science, Eskisehir Osmangazi University, Eskisehir, Turkey.
  • Ahmet Faruk Aslan
    Department of Mathematics and Computer Science, Faculty of Science, Eskisehir Osmangazi University, Eskisehir, Turkey.
  • Rohan Jagtap
    Division of Oral and Maxillofacial Radiology, Department of Care Planning and Restorative Sciences, University of Mississippi Medical Center (UMMC) School of Dentistry, Jackson, MS, United States.

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