Deep Learning-based Assessment of Facial Asymmetry Using U-Net Deep Convolutional Neural Network Algorithm.

Journal: The Journal of craniofacial surgery
PMID:

Abstract

OBJECTIVES: This study aimed to evaluate the diagnostic performance of a deep convolutional neural network (DCNN)-based computer-assisted diagnosis (CAD) system to detect facial asymmetry on posteroanterior (PA) cephalograms and compare the results of the DCNN with those made by the orthodontist.

Authors

  • Sang-Min Jeon
    California Dental Clinic, Gwangju, Korea.
  • Seojeong Kim
    Korea Electronics Technology Institute, Seongnam, Korea.
  • Kyungmin Clara Lee
    Department of Orthodontics, School of Dentistry, Chonnam National University, 33 Yongbong-ro, Buk-gu, Gwangju, 61186, Republic of Korea. ortholkm@jnu.ac.kr.