A Fully Automated Analytic System for Measuring Endolymphatic Hydrops Ratios in Patients With Ménière Disease via Magnetic Resonance Imaging: Deep Learning Model Development Study.

Journal: Journal of medical Internet research
PMID: 34546181

Abstract

BACKGROUND: Recently, the analysis of endolymphatic hydropses (EHs) via inner ear magnetic resonance imaging (MRI) for patients with Ménière disease has been attempted in various studies. In addition, artificial intelligence has rapidly been incorporated into the medical field. In our previous studies, an automated algorithm for EH analysis was developed by using a convolutional neural network. However, several limitations existed, and further studies were conducted to compensate for these limitations.

Authors

  • Chae Jung Park
    Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Seoul, Republic of Korea.
  • Young Sang Cho
    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.).
  • Yi-Kyung Kim
    Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
  • Hyung-Jin Kim
    Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
  • Kyunga Kim
    Statistics and Data Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, Republic of Korea.
  • Jae-Wook Ko
    Department of Clinical Pharmacology and Therapeutics, Samsung Medical Center, Seoul, Republic of Korea.
  • Won-Ho Chung
    Department of Otorhinolaryngology-Head and Neck Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
  • Baek Hwan Cho
    Smart Healthcare & Device Research Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.

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