Dense Convolutional Network and Its Application in Medical Image Analysis | Zendy

Tao Zhou | Zendy; Xinyu Ye | Zendy; Huiling Lu | Zendy; Xiaomin Zheng | Zendy; Shi Qiu | Zendy; YunCan Liu | Zendy

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Dense Convolutional Network and Its Application in Medical Image Analysis

Author(s) -

Tao Zhou,

Xinyu Ye,

Huiling Lu,

Xiaomin Zheng,

Shi Qiu,

YunCan Liu

Publication year - 2022

Publication title -

biomed research international

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.772

H-Index - 126

eISSN - 2314-6141

pISSN - 2314-6133

DOI - 10.1155/2022/2384830

Subject(s) - computer science , artificial intelligence , image (mathematics) , convolutional neural network , field (mathematics) , segmentation , pattern recognition (psychology) , mathematics , pure mathematics

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.

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