ResNet and Its Application to Medical Image Processing: Research Progress and Challenges

ZHOU Tao; LIU Yuncan; LU Huiling; YE Xinyu; CHANG Xiaoyu

doi:10.11999/JEIT210914

Volume 44 Issue 1

Jan. 2022

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Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(1): 149-167

ZHOU Tao, LIU Yuncan, LU Huiling, YE Xinyu, CHANG Xiaoyu. ResNet and Its Application to Medical Image Processing: Research Progress and Challenges[J]. Journal of Electronics & Information Technology, 2022, 44(1): 149-167. doi: 10.11999/JEIT210914

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ZHOU Tao, LIU Yuncan, LU Huiling, YE Xinyu, CHANG Xiaoyu. ResNet and Its Application to Medical Image Processing: Research Progress and Challenges[J]. Journal of Electronics & Information Technology, 2022, 44(1): 149-167. doi: 10.11999/JEIT210914

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ResNet and Its Application to Medical Image Processing: Research Progress and Challenges

doi: 10.11999/JEIT210914

ZHOU Tao^{1, 2},
LIU Yuncan^{1
,
,},
LU Huiling³,
YE Xinyu¹,
CHANG Xiaoyu¹

1.
School of Computer Science and Engineering, North Minzu University, Yinchuan 750021, China
2.
Key Laboratory of Image and Graphics Intelligent Processing of State Ethnic Affairs Commission, North Minzu University, Yinchuan 750021, China
3.
School of Science, Ningxia Medical University, Yinchuan 750004, China

Funds: The National Natural Science Foundation of China (62062003), The Key R&D Plan of Ningxia Autonomous Region (2020BEB04022), The Introduction of Talents and Scientific Research Start-Up Project of North Minzu University (2020KYQD08), The 2020 Graduate Innovation Project of North Minzu University (YCX21089)

Received Date: 2021-08-31
Accepted Date: 2021-12-24
Rev Recd Date: 2021-12-24

Available Online: 2022-01-04

Publish Date: 2022-01-10

Abstract

Abstract

Residual neural Network (ResNet) is a hot topic in deep learning research, which is widely used in medical image processing. The residual neural network is reviewed in this paper from the following aspects: Firstly, the basic principles and model structure of residual neural network are explained; Secondly, the improvement mechanisms of residual neural network are summarized from three aspects of residual unit, residual connection and the entire network structure; Thirdly, the wide applications of residual neural network to medical image processing are discussed from four aspects combining DenseNet, U-Net, Inception structure and attention mechanism; Finally, the main challenges that ResNet faces in medical image processing are discussed, and the future development direction is prospected. In this paper, the latest research progress of residual neural network and its application to medical image processing are systematically sorted out, which has important reference value for the research of residual neural network.
- Residual neural Network (ResNet),
- Medical image,
- Residual unit,
- Residual connection,
- Activation function

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References(98)

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