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Lung diseases identification method based on capsule neural network

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成果类型:
期刊论文
作者:
Zhao, Di;Liu, Jing;Zhou, Guo-Xiong
通讯作者:
Liu, Jing(14915443@qq.com)
作者机构:
[Zhao, Di] School of Information Science and Engineering, Hunan First Normal University, Hunan, Changsha
410205, China
[Liu, Jing] Department of Information Engineering, Hunan Vocational College of Engineering, Hunan, Changsha
410151, China
[Zhou, Guo-Xiong] School of Computer and Information Engineering, Central South Forestry University, Hunan, Changsha
通讯机构:
[Jing Liu] D
Department of Information Engineering, Hunan Vocational College of Engineering, Changsha, China
语种:
英文
关键词:
Capsule neural network;Data enhancement;Image preprocessing;Lung diseases identification
期刊:
Evolutionary Intelligence
ISSN:
1864-5909
年:
2022
卷:
15
期:
4
页码:
2375-2384
机构署名:
本校为其他机构
院系归属:
计算机与信息工程学院
摘要:
In the automatic identification of lesions, aiming at the misdiagnosis of the lung nodule size, shape, blood vessels and other lung tissues on CT images of pneumonia, this paper proposes a method for identifying lung diseases based on capsule neural networks. Considering that the texture features of lung CT images contain important medical information, this article first combines gray average, entropy, fractal dimension and fractal intercept to form feature vectors as texture features, and introduces context models to obtain context information...

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