Dense Convolutional Network and Its Application in Medical Image Analysis.

Journal: BioMed research international
Published Date: Apr 25, 2022

Abstract

Dense convolutional network (DenseNet) is a hot topic in deep learning research in recent years, which has good applications in medical image analysis. In this paper, DenseNet is summarized from the following aspects. First, the basic principle of DenseNet is introduced; second, the development of DenseNet is summarized and analyzed from five aspects: broaden DenseNet structure, lightweight DenseNet structure, dense unit, dense connection mode, and attention mechanism; finally, the application research of DenseNet in the field of medical image analysis is summarized from three aspects: pattern recognition, image segmentation, and object detection. The network structures of DenseNet are systematically summarized in this paper, which has certain positive significance for the research and development of DenseNet.

Authors

  • Tao Zhou
    Department of Otorhinolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
  • XinYu Ye
    School of Computer Science and Engineering, North Minzu University, Yinchuan 750021, China.
  • Huiling Lu
    School of Science, Ningxia Medical University, Ningxia, Yinchuan 750004, China.
  • Xiaomin Zheng
    Department of Radiation and Medical Oncology, The 1st Affiliated Hospital of Wenzhou Medical University, No.2 Fuxue Lane, Wenzhou, 325000, People's Republic of China.
  • Shi Qiu
    Key Laboratory of Spectral Imaging Technology CAS, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an 710119, China.
  • YunCan Liu
    School of Computer Science and Engineering, North Minzu University, Yinchuan 750021, China.

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