Deep learning for automatic diagnosis of gastric dysplasia using whole-slide histopathology images in endoscopic specimens.

Journal: Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
Published Date: Apr 8, 2022

Abstract

BACKGROUND: Distinguishing gastric epithelial regeneration change from dysplasia and histopathological diagnosis of dysplasia is subject to interobserver disagreement in endoscopic specimens. In this study, we developed a method to distinguish gastric epithelial regeneration change from dysplasia and further subclassify dysplasia. Meanwhile, optimized the cross-hospital diagnosis using domain adaption (DA).

Authors

  • Zhongyue Shi
    Department of Pathology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, 100020, China.
  • Chuang Zhu
    The Center for Data Science, the Beijing Key Laboratory of Network System Architecture and Convergence, the School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Xitucheng Road, Beijing, China. czhu@bupt.edu.cn.
  • Yu Zhang
    College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.
  • Yakun Wang
    College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
  • Weihua Hou
    Department of Pathology, PLA Joint Logistics Support Force 989 Hospital (Formerly, the 152 Central Hospital), Henan, China.
  • Xue Li
    Department of Clinical Research Center, Dazhou Central Hospital, Dazhou 635000, China.
  • Jun Lu
    School of Acupuncture-moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing 100029, China.
  • Xinmeng Guo
    Department of Pathology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, 100020, China.
  • Feng Xu
    Orthopedics Department of the First Affiliated Hospital of Tsinghua University, Beijing, China.
  • Xingran Jiang
    Department of Pathology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, 100020, China.
  • Ying Wang
    Key Laboratory of Macromolecular Science of Shaanxi Province, School of Chemistry & Chemical Engineering, Shaanxi Normal University, Xi'an, Shaanxi 710062, China.
  • Jun Liu
    Department of Radiology, Second Xiangya Hospital, Changsha, Hunan, China.
  • Mulan Jin
    Department of Pathology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, 100020, China. kinmokuran@163.com.

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