Detection of maxillary sinus fungal ball via 3-D CNN-based artificial intelligence: Fully automated system and clinical validation.

Journal: PloS one
PMID:

Abstract

BACKGROUND: This study aims to develop artificial intelligence (AI) system to automatically classify patients with maxillary sinus fungal ball (MFB), chronic rhinosinusitis (CRS), and healthy controls (HCs).

Authors

  • Kyung-Su Kim
    Medical AI Research Center, Samsung Medical Center, Seoul, Republic of Korea.
  • Byung Kil Kim
    Department of Otorhinolaryngology-Head and Neck Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
  • Myung Jin Chung
    From the Department of Radiology, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea (Y.S., K.H., B.W.C.); Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea (M.J.C.); Department of Radiology, University Medical Center Freiburg, Freiburg, Germany (E.K.); Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Mass (S. Yune, M.K., S.D.); and Samsung Electronics, Suwon, Republic of Korea (H.K., S. Yang, D.J.L.).
  • Hyun Bin Cho
    Medical AI Research Center, Samsung Medical Center, Seoul, Republic of Korea.
  • Beak Hwan Cho
    Medical AI Research Center, Samsung Medical Center, Seoul, Republic of Korea.
  • Yong Gi Jung
    Medical AI Research Center, Samsung Medical Center, Seoul, Republic of Korea.