计算机应用与软件2024，Vol.41Issue(7)：177-183,7.DOI:10.3969/j.issn.1000-386x.2024.07.027
基于RDU-Net网络的肺部CT分割算法研究
LUNG CT SEGMENTATION ALGORITHM BASED ON RDU-NET NETWORK
陈亚浩 1韩林 2刘艳青 2张悦1
作者信息
- 1. 郑州大学信息工程学院 河南郑州 450000
- 2. 国家超级计算郑州中心 河南郑州 450052
- 折叠
摘要
Abstract
This paper proposes the RDU-Net network to segment lung nodules.The network is based on the U-Net network.Aimed at the phenomenon of gradient disappearance that often occurred during network training,the residual unit was introduced to improve the basic network.This operation solved the problem of gradient disappearance during the network model training process.In order to improve the generalization ability of the network,a Dropout layer was added to the network to avoid overfitting during the training process and further improve the segmentation accuracy.The network was tested on the LIDC-IDRI dataset,and its AUC and Dice reached 0.89 and 0.76,respectively.Compared with the basic network,its segmentation accuracy and segmentation effect were improved to a certain extent.关键词
深度学习/U-Net/肺片分割/肺结节Key words
Deep learning/U-Net/Lung slice segmentation/Lung nodules分类
信息技术与安全科学引用本文复制引用
陈亚浩,韩林,刘艳青,张悦..基于RDU-Net网络的肺部CT分割算法研究[J].计算机应用与软件,2024,41(7):177-183,7.
