Dense Convolutional Network and Its Application in Medical Image Analysis

Author:

Zhou Tao12ORCID,Ye XinYu12ORCID,Lu HuiLing3ORCID,Zheng Xiaomin4,Qiu Shi5,Liu YunCan12

Affiliation:

1. School of Computer Science and Engineering, North Minzu University, Yinchuan 750021, China

2. Key Laboratory of Image & Graphics Intelligent Processing of State Ethnic Affairs Commission, North Minzu University, Yinchuan 750021, China

3. School of Science, Ningxia Medical University, Yinchuan 750004, China

4. Research Institute for Reproductive Medicine and Genetic Diseases, Wuxi Maternity and Child Health Hospital, Wuxi, Jiangsu 214002, China

5. Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an 710119, China

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.

Funder

North Minzu University

Publisher

Hindawi Limited

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine

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