Style harmonization of panoramic radiography using deep learning.

Journal: Oral radiology
PMID: 39470914

Abstract

OBJECTIVES: This study aimed to harmonize panoramic radiograph images from different equipment in a single institution to display similar styles.

Authors

  • Hak-Sun Kim
    Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea.
  • Jaejung Seol
    Graduate School of Artificial Intelligence, Ulsan National Institute of Science and Technology, 50 UNIST-Gil, Ulsan, 44919, Republic of Korea.
  • Ji-Yun Lee
    Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, 50-1 Yonsei-Ro, Seodaemun-Gu, Seoul, 03722, Republic of Korea.
  • Sang-Sun Han
    Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea. Electronic address: sshan@yuhs.ac.
  • Jaejun Yoo
    Department of Bio and Brain Engineering, Korea Advanced Institute of Science & Technology (KAIST), Daejeon, Republic of Korea.
  • Chena Lee
    Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea.

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