C. Guan, S. Wang, A.W.C. Liew, July 2020, Lip image segmentation based on a fuzzy convolutional neural network, IEEE Transactions on Fuzzy Systems, Vol. 28, No. 7, pp. 1242-1251

J. Long, E. Shelhamer, T. Darrell, 2015, Fully Convolutional Networks for Semantic Segmentation, The IEEE Conference on Computer Vision and Pattern Recognition, pp. 3431-3440

O. Ronneberger, P. Fischer, T. Brox, 2015, U-net: Convolutional networks for biomedical image segmentation, International Conference on Medical image computing and computer- assisted intervention, pp. 234-241

Z.W. Zhou, M.M.R. Siddiquee, N. Tajbakhsh, J.M. Liang, 2018, UNet++: A Nested U-Net Architecture for Medical Image Segmentation, Deep Learning in Medical Image Anylysis and Multimodal Learning for Clinical Decision Support, pp. 3-11

Huimin Huang, 2020, Unet 3+: A full-scale connected unet for medical image segmentatio, 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1055-1059

Tae-Hoon Kim, Jong-Jin Park, 2023．, Teeth Segmentation for Orthodontics based on Deep Learning, The Transactions of the Korean Institute of Electrical Engineers, Vol. 72, No. 3, pp. 440-446

Yo-wei Chen, March 2020, Artificial intelligence in dentistry: current applications and future perspectives, QUINTESSENCE INTERNATIONAL, Vol. 51, No. 3

Sang-Sun Han, May 2022, Trend of Artificial Intelligence technology in oral and maxillofacial radiology, The Journal of the Korean Dental Association (JKDA), Vol. 60, No. 5

Tae Jun Jang, Kang Cheol Kim, Hyun Cheol Cho, Jin Keun Seo, OCTOBER 2022, A Fully Automated Method for 3D Individual Tooth Identification and Segmentation in Dental CBCT, IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, Vol. 44, No. 10

Z. Cui, Y. Fang, L. Mei, 2022, A fully automatic AI system for tooth and alveolar bone segmentation from cone-beam CT images, Nature Communications, Vol. 13, No. 2096

https://www.aihub.or.kr/,

F Pesapane, M Codari, F. Sardanelli, 2018 Oct, Artificial intelligence in medical imaging: Threat or opportunity? Radiologists again at the forefront of innovation in medicine, Eur Radiol Exp, Vol. 2, No. 1, pp. 35