Fully-channel regional attention network for disease-location recognition with tongue images.

Journal: Artificial intelligence in medicine
Published Date: May 26, 2021

Abstract

OBJECTIVE: Using the deep learning model to realize tongue image-based disease location recognition and focus on solving two problems: 1. The ability of the general convolution network to model detailed regional tongue features is weak; 2. Ignoring the group relationship between convolution channels, which caused the high redundancy of the model.

Authors

  • Yang Hu
    Kweichow Moutai Co., Ltd, Renhuai, Guizhou 564501, China.
  • Guihua Wen
    School of Computer Science and Engineering, South China University of Technology, Guangzhou 510000, China. Electronic address: crghwen@scut.edu.cn.
  • Mingnan Luo
    School of Computer Science & Engineering, South China University of Technology, Guangzhou, China; Guangdong Engineering Technology Research Center for Artificial intelligence and traditional Chinese Medicine, Guangzhou, China.
  • Pei Yang
    Department of Bone and Joint Surgery, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
  • Dan Dai
  • Zhiwen Yu
  • Changjun Wang
    Guangdong General Hospital, Guangzhou 510000, China. Electronic address: gzwchj@126.com.
  • Wendy Hall
    University of Southampton, Highfield Campus, SO171BJ Southampton, United Kingdom. Electronic address: wh@ecs.soton.ac.uk.

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