Login / Signup

Development of an artificial intelligence-based algorithm to classify images acquired with an intraoral scanner of individual molar teeth into three categories.

Nozomi EtoJunichi YamazoeAkiko TsujiNaohisa WadaNoriaki Ikeda
Published in: PloS one (2022)
We have created an artificial intelligence-based algorithm that analyzes images acquired with an intraoral scanner and classifies molar teeth into one of three types (FMC, In or CNMR) based on the presence/absence of metallic restorations. Furthermore, the accuracy of the algorithm reached about 95%. This algorithm was constructed as a first step toward the development of an automated system that generates dental charts from images acquired by an intraoral scanner. The availability of such a system would greatly increase the efficiency of personal identification in the event of a major disaster.
Keyphrases
  • deep learning
  • artificial intelligence
  • machine learning
  • convolutional neural network
  • big data
  • image quality
  • magnetic resonance imaging
  • cone beam computed tomography
  • clinical evaluation