Performance of a Convolutional Neural Network-Based Artificial Intelligence Algorithm for Automatic Cephalometric Landmark Detection

UĞURLU M.

TURKISH JOURNAL OF ORTHODONTICS, vol.35, no.2, pp.94-100, 2022 (ESCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 35 Issue: 2
  • Publication Date: 2022
  • Doi Number: 10.5152/turkjorthod.2022.22026
  • Journal Name: TURKISH JOURNAL OF ORTHODONTICS
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus
  • Page Numbers: pp.94-100
  • Keywords: Anatomic landmark, lateral cephalometric radiograph, deep learning, artificial intelligence
  • Eskisehir Osmangazi University Affiliated: Yes

Abstract

Objective: The aim of this study is to develop an artificial intelligence model to detect cephalometric landmark automatically enabling the automatic analysis of cephalometric radiographs which have a very important place in dental practice and is used routinely in the diagnosis and treatment of dental and skeletal disorders.