Development and validation of a clinically applicable deep learning strategy (HONORS) for pulmonary nodule classification at CT: A retrospective multicentre study.

Journal: Lung cancer (Amsterdam, Netherlands)
Published Date:

Abstract

PURPOSE: To propose a practical strategy for the clinical application of deep learning algorithm, i.e., Hierarchical-Ordered Network-ORiented Strategy (HONORS), and a new approach to pulmonary nodule classification in various clinical scenarios, i.e., Filter-Guided Pyramid NETwork (FGP-NET).

Authors

  • Wenhui Lv
    Department of Medical Imaging, Jinling Hospital, Southern Medical University, No.305, Zhongshan East Road, Nanjing, 210002, China.
  • Yang Wang
    Department of General Surgery The First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology Kunming China.
  • Changsheng Zhou
    Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, No.305, Zhongshan East Road, Nanjing, 210002, China.
  • Mei Yuan
  • Minxia Pang
    Department of CT, Shengli Oilfield Central Hospital, Dongying, China.
  • Xiangming Fang
    Imaging Center, Wuxi People's Hospital, Nanjing Medical University, Wuxi, 214000, China. Electronic address: drfxm@163.com.
  • Qirui Zhang
    Department of Medical Imaging, Jinling Hospital, Southern Medical University, No.305, Zhongshan East Road, Nanjing, 210002, China.
  • Chuxi Huang
    Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, No.305, Zhongshan East Road, Nanjing, 210002, China.
  • Xinyu Li
    School of Pharmacy, Binzhou Medical University, Yantai, China.
  • Zhen Zhou
    Deepwise Healthcare, Beijing 100080, China.
  • Yizhou Yu
    Department of Computer Science, The University of Hong Kong, Pok Fu Lam, Hong Kong.
  • Yizhou Wang
  • Mengjie Lu
    Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, 210002, Jiangsu, China.
  • Qiang Xu
    University of Huddersfield, Queensgate, Huddersfield, United Kingdom . Electronic address: Q.Xu2@hud.ac.uk.
  • Xiuli Li
    Department of Obstetrics and Gynecology, General Hospital of Chinese People's Liberation Army, Beijing 100853, China.
  • Haoliang Lin
    Deepwise AI Lab, Deepwise Inc., Beijing, China.
  • Xiaofan Lu
    Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, China.
  • Qinmei Xu
    Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, No.305, Zhongshan East Road, Nanjing, 210002, China.
  • Jing Sun
    Department of Gastroenterology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Yuxia Tang
    Department of Diagnostic Radiology, Jinling Hospital, Medical School of Nanjing University, Nanjing, China.
  • Fangrong Yan
    Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, China.
  • Bing Zhang
    School of Information Science and Engineering, Yanshan University, Hebei Avenue, Qinhuangdao, 066004, China.
  • Zhen Cheng
    College of Food Science, Shenyang Agriculture University, Shenyang, Liaoning 110866, China.
  • Longjiang Zhang
    Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, No.305, Zhongshan East Road, Nanjing, 210002, China.
  • Guangming Lu
    Department of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China.