Automatic Multilabel Classification of Multiple Fundus Diseases Based on Convolutional Neural Network With Squeeze-and-Excitation Attention.

Journal: Translational vision science & technology
Published Date: Jan 3, 2023

Abstract

PURPOSE: Automatic multilabel classification of multiple fundus diseases is of importance for ophthalmologists. This study aims to design an effective multilabel classification model that can automatically classify multiple fundus diseases based on color fundus images.

Authors

  • Zhenzhen Lu
    Department of Biomedical Engineering, Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing University of Technology, Beijing, China.
  • Jingpeng Miao
    Beijing Tongren Eye Center, Beijing Ophthalmology & Visual Sciences Key Lab, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
  • Jingran Dong
    Department of Biomedical Engineering, Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing University of Technology, Beijing, China.
  • Shuyuan Zhu
    Department of Biomedical Engineering, Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing University of Technology, Beijing, China.
  • Penghan Wu
    Fan Gongxiu Honors College, Beijing University of Technology, Beijing, China.
  • Xiaobing Wang
    Sports and Medicine Integrative Innovation Center, Capital University of Physical Education and Sports, Beijing, China.
  • Jihong Feng
    Department of Biomedical Engineering, Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing University of Technology, Beijing, China.

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