A deep learning-based segmentation system for rapid onsite cytologic pathology evaluation of pancreatic masses: A retrospective, multicenter, diagnostic study.

Journal: EBioMedicine
PMID:

Abstract

BACKGROUND: We aimed to develop a deep learning-based segmentation system for rapid on-site cytopathology evaluation (ROSE) to improve the diagnostic efficiency of endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) biopsy.

Authors

  • Song Zhang
    College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
  • Yangfan Zhou
    National Institute of Healthcare Data Science at Nanjing University, Nanjing, Jiangsu 210008, China; National Key Laboratory for Novel Software Technology, Department of Computer Science and Technology, Nanjing University, Nanjing, Jiangsu 210008, China.
  • Dehua Tang
    Department of Gastroenterology, Nanjing Drum Tower Hospital, Affiliated Drum Tower Hospital, Medical School of Nanjing University, 321 Zhongshan Road, Nanjing, Jiangsu 210008, China.
  • Muhan Ni
    Department of Gastroenterology, Nanjing Drum Tower Hospital, Affiliated Drum Tower Hospital, Medical School of Nanjing University, 321 Zhongshan Road, Nanjing, Jiangsu 210008, China.
  • Jinyu Zheng
    Institute of rehabilitation engineering and technology, University of Shanghai for Science and Technology.
  • Guifang Xu
    Department of Gastroenterology, Nanjing Drum Tower Hospital, Affiliated Drum Tower Hospital, Medical School of Nanjing University, 321 Zhongshan Road, Nanjing, Jiangsu 210008, China. Electronic address: 13852293376@163.com.
  • Chunyan Peng
    Department of Gastroenterology, Nanjing Drum Tower Hospital, Clinical College of Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210008, China; Department of Gastroenterology, Nanjing Drum Tower Hospital, Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu 210008, China.
  • Shanshan Shen
    Department of Gastroenterology, Nanjing Drum Tower Hospital, Clinical College of Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210008, China; Department of Gastroenterology, Nanjing Drum Tower Hospital, Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu 210008, China.
  • Qiang Zhan
    Department of Gastroenterology, Wuxi People's Hospital, Affiliated Wuxi People's Hospital with Nanjing Medical University, Wuxi, Jiangsu 214023, China.
  • Xiaoyun Wang
    College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China; The Key Laboratory of Western China's Environmental Systems, Ministry of Education (MOE), Lanzhou 730000, China.
  • Duanmin Hu
    Department of Gastroenterology, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215004, China.
  • Wu-Jun Li
    National Institute of Healthcare Data Science at Nanjing University, Nanjing, Jiangsu 210008, China; National Key Laboratory for Novel Software Technology, Department of Computer Science and Technology, Nanjing University, Nanjing, Jiangsu 210008, China; Center for Medical Big Data, Nanjing Drum Tower Hospital, Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu 210008, China. Electronic address: liwujun@nju.edu.cn.
  • Lei Wang
    Department of Nursing, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
  • Ying Lv
    Department of Gastroenterology, Nanjing Drum Tower Hospital, Affiliated Drum Tower Hospital, Medical School of Nanjing University, 321 Zhongshan Road, Nanjing, Jiangsu 210008, China.
  • Xiaoping Zou
    Department of Gastroenterology, Nanjing Drum Tower Hospital of Nanjing University, Nanjing, China.