Squeeze-and-Excitation Convolutional Neural Network for Classification of Malignant and Benign Lung Nodules

被引：7
|
作者：
Chen, Ying [1 ]
Du, Weiwei [2 ]
Duan, Xiaojie [1 ]
Ma, Yanhe [3 ]
Zhang, Hong [3 ]
机构：
[1] Tiangong Univ, Sch Elect & Informat Engn, Tianjin, Peoples R China
[2] Kyoto Inst Technol, Dept Informat & Human Sci, Kyoto, Japan
[3] Tianjin Chest Hosp, Tianjin, Peoples R China
来源：
JOURNAL OF ADVANCES IN INFORMATION TECHNOLOGY | 2021年 / 12卷 / 02期
关键词：
squeeze-and-excitation convolutional network; classify; lung nodules; the LIDC-IDRI database;
D O I：
10.12720/jait.12.2.153-158
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Lung cancer is the world's highest morbidity and mortality cancer, which seriously threatens the life and health of the public. Early detection and diagnosis of lung nodules is an important prerequisite for lung cancer prevention and diagnosis. This paper designs a new structure which is a Squeeze-and-Excitation Convolutional Neural Network. Experimental results show that SE-CNN can recognize the benign and malignant lung nodules. SE-CNN is more effective than CNN for classification of benign and malignant lung nodules.
引用
收藏
页码：153 / 158
页数：6
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