A deep learning approach to dental restoration classification from bitewing and periapical radiographs.

Journal: Quintessence international (Berlin, Germany : 1985)
Published Date:

Abstract

OBJECTIVE: The aim of this study was to examine the success of deep learning-based convolutional neural networks (CNN) in the detection and differentiation of amalgam, composite resin, and metal-ceramic restorations from bitewing and periapical radiographs.

Authors

  • Ozcan Karatas
  • Nazire Nurdan Cakir
  • Saban Suat Ozsariyildiz
  • Hatice Cansu Kis
  • Sezer Demirbuga
  • Cem Abdulkadir Gurgan