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Dense Convolutional Network and Its Application in Medical Image Analysis

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 D...

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Detalles Bibliográficos
Autores principales: Zhou, Tao, Ye, XinYu, Lu, HuiLing, Zheng, Xiaomin, Qiu, Shi, Liu, YunCan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9060995/
https://www.ncbi.nlm.nih.gov/pubmed/35509707
http://dx.doi.org/10.1155/2022/2384830
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author Zhou, Tao
Ye, XinYu
Lu, HuiLing
Zheng, Xiaomin
Qiu, Shi
Liu, YunCan
author_facet Zhou, Tao
Ye, XinYu
Lu, HuiLing
Zheng, Xiaomin
Qiu, Shi
Liu, YunCan
author_sort Zhou, Tao
collection PubMed
description 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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spelling pubmed-90609952022-05-03 Dense Convolutional Network and Its Application in Medical Image Analysis Zhou, Tao Ye, XinYu Lu, HuiLing Zheng, Xiaomin Qiu, Shi Liu, YunCan Biomed Res Int Review Article 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. Hindawi 2022-04-25 /pmc/articles/PMC9060995/ /pubmed/35509707 http://dx.doi.org/10.1155/2022/2384830 Text en Copyright © 2022 Tao Zhou et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review Article
Zhou, Tao
Ye, XinYu
Lu, HuiLing
Zheng, Xiaomin
Qiu, Shi
Liu, YunCan
Dense Convolutional Network and Its Application in Medical Image Analysis
title Dense Convolutional Network and Its Application in Medical Image Analysis
title_full Dense Convolutional Network and Its Application in Medical Image Analysis
title_fullStr Dense Convolutional Network and Its Application in Medical Image Analysis
title_full_unstemmed Dense Convolutional Network and Its Application in Medical Image Analysis
title_short Dense Convolutional Network and Its Application in Medical Image Analysis
title_sort dense convolutional network and its application in medical image analysis
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9060995/
https://www.ncbi.nlm.nih.gov/pubmed/35509707
http://dx.doi.org/10.1155/2022/2384830
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