Generative adversarial networks in dental imaging: a systematic review.

Sujin Yang Kee-Deog Kim Eiichiro Ariji Yoshitaka Kise

Published in: Oral radiology (2023)

This extensive analysis of GANs in dental imaging highlighted their broad application potential within the dental field. Future studies should address limitations related to the stability, repeatability, and overall interpretability of GAN architectures. By overcoming these challenges, the applicability of GANs in dentistry can be enhanced, ultimately benefiting the dental field in its use of GANs and artificial intelligence.

Keyphrases

artificial intelligence
oral health
high resolution
machine learning
big data
deep learning
risk assessment
human health
fluorescence imaging
photodynamic therapy
drug induced