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A fully deep learning model for the automatic identification of cephalometric landmarks.

Young Hyun KimChena LeeEun-Gyu HaYoon Jeong ChoiSang-Sun Han
Published in: Imaging science in dentistry (2021)
This experiment demonstrated that the proposed deep learning model can perform fully automatic identification of cephalometric landmarks and achieve better results than examiners for some landmarks. It is meaningful to consider between-examiner variability for clinical applicability when evaluating the performance of deep learning methods in cephalometric landmark identification.
Keyphrases
  • deep learning
  • artificial intelligence
  • convolutional neural network
  • machine learning
  • bioinformatics analysis