A novel Joint-Net model for recognizing small-bowel polyp images.

Journal: Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy
Published Date:

Abstract

INTRODUCTION: To automatically recognize polyps of enteroscopy images and avoid pathological change, a novel Joint-Net has been proposed.

Authors

  • Xudong Guo
    School of Medical Instruments and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
  • Shengnan Li
    Guangzhou F.Q.PATHOTECH Co., Ltd, Guangzhou, Guangdong Province, PR China.
  • Linqi Zhang
    School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, China.
  • Yuxin Wang
    The Key Laboratory of Food Safety Risk Assessment, Ministry of Health, China National Center for Food Safety Risk Assessment, Beijing 100021, China. Electronic address: wangyx@cfsa.net.cn.
  • Lulu Zhang
    Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, 100700, People's Republic of China.
  • Zhang Liu
    School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, China.
  • Jiefang Guo
    Department of Gastroenterology, Changhai Hospital, Shanghai, 200433, China.
  • Yiqi Du
    Department of Gastroenterology, Changhai Hospital, Naval Medical University, Shanghai, China.