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The Angle Orthodontist|December 30, 2020
Evaluation of an automated superimposition method for computer-aided cephalometricsJun-Ho Moon, Hye-Won Hwang, Shin-Jae Lee
The Angle Orthodontist|January 12, 2021
Evaluation of automated cephalometric analysis based on the latest deep learning methodHye-Won Hwang, Jun-Ho Moon, Min-Gyu Kim, et al.
The Angle Orthodontist|December 30, 2020
How much deep learning is enough for automatic identification to be reliable?Jun-Ho Moon, Hye-Won Hwang, Youngsung Yu, et al.
The Angle Orthodontist|October 4, 2021
Evaluation of an automated superimposition method based on multiple landmarks for growing patientsMin-Gyu Kim, Jun-Ho Moon, Hye-Won Hwang, et al.
The Angle Orthodontist|August 18, 2022
Evaluation of an individualized facial growth prediction model based on the multivariate partial least squares methodJun-Ho Moon, Min-Gyu Kim, Hye-Won Hwang, et al.
The Angle Orthodontist|August 24, 2024
Evaluation of automated photograph-cephalogram image integration using artificial intelligence modelsJun-Ho Moon, Min-Gyu Kim, Sung Joo Cho, et al.
The Angle Orthodontist|July 9, 2019
Automated identification of cephalometric landmarks: Part 1-Comparisons between the latest deep-learning methods YOLOV3 and SSDJi-Hoon Park, Hye-Won Hwang, Jun-Ho Moon, et al.
The Angle Orthodontist|July 24, 2019
Automated identification of cephalometric landmarks: Part 2-Might it be better than human?Hye-Won Hwang, Ji-Hoon Park, Jun-Ho Moon, et al.
The Angle Orthodontist|January 12, 2025
Craniofacial growth prediction models based on cephalometric landmarks in Korean and American childrenJong-Hak Kim, Jun-Ho Moon, Jeffrey Roseth, et al.
Orthodontics & Craniofacial Research|May 7, 2024
Factors influencing the development of artificial intelligence in orthodonticsJu-Myung Lee, Jun-Ho Moon, Ji-Ae Park, et al.
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