Generative adversarial networks in dental imaging: a systematic review.

Journal: Oral radiology
PMID: 38001347

Abstract

OBJECTIVES: This systematic review on generative adversarial network (GAN) architectures for dental image analysis provides a comprehensive overview to readers regarding current GAN trends in dental imagery and potential future applications.

Authors

  • Sujin Yang
    Department of Advanced General Dentistry, College of Dentistry, Yonsei University, Seoul, Republic of Korea.
  • Kee-Deog Kim
    Department of Advanced General Dentistry, College of Dentistry, Yonsei University, Seoul, Republic of Korea.
  • Eiichiro Ariji
    Department of Oral and Maxillofacial Radiology, Aichi Gakuin University School of Dentistry, Nagoya, Japan.
  • Yoshitaka Kise
    Department of Oral and Maxillofacial Radiology, Aichi Gakuin University School of Dentistry, Nagoya, Japan.

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