Deep learning for abdominal ultrasound: A computer-aided diagnostic system for the severity of fatty liver.

Journal: Journal of the Chinese Medical Association : JCMA
PMID: 34282076

Abstract

BACKGROUND: The prevalence of nonalcoholic fatty liver disease is increasing over time worldwide, with similar trends to those of diabetes and obesity. A liver biopsy, the gold standard of diagnosis, is not favored due to its invasiveness. Meanwhile, noninvasive evaluation methods of fatty liver are still either very expensive or demonstrate poor diagnostic performances, thus, limiting their applications. We developed neural network-based models to assess fatty liver and classify the severity using B-mode ultrasound (US) images.

Authors

  • Tsung-Hsien Chou
    Division of Gastroenterology and Hepatology, Department of Internal Medicine, Taipei Medical University Hospital, Taipei, Taiwan, ROC.
  • Hsing-Jung Yeh
    Division of Gastroenterology and Hepatology, Department of Internal Medicine, Taipei Medical University Hospital, Taipei, Taiwan, ROC.
  • Chun-Chao Chang
    Division of Gastroenterology and Hepatology, Department of Internal Medicine, Taipei Medical University Hospital, Taipei, Taiwan, ROC.
  • Jui-Hsiang Tang
    Division of Gastroenterology and Hepatology, Department of Internal Medicine, Taipei Medical University Hospital, Taipei, Taiwan, ROC.
  • Wei-Yu Kao
    Division of Gastroenterology and Hepatology, Department of Internal Medicine, Taipei Medical University Hospital, Taipei, Taiwan, ROC.
  • I-Chia Su
    Division of Gastroenterology and Hepatology, Department of Internal Medicine, Taipei Medical University Hospital, Taipei, Taiwan, ROC.
  • Chien-Hung Li
    Acer Value Lab Advanced Tech Business Unit, Acer Incorporated, New Taipei City, Taiwan, ROC.
  • Wei-Hao Chang
    Acer Value Lab Advanced Tech Business Unit, Acer Incorporated, New Taipei City, Taiwan, ROC.
  • Chun-Kai Huang
  • Herdiantri Sufriyana
    Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan; Department of Medical Physiology, College of Medicine, University of Nahdlatul Ulama Surabaya, Surabaya 60237, Indonesia. Electronic address: herdiantrisufriyana@unusa.ac.id.
  • Emily Chia-Yu Su
    Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan. emilysu@tmu.edu.tw.

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