Detection of low dose CT pulmonary nodules based on 3D convolution neural network-Reference-Cited by-同舟云学术

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Detection of low dose CT pulmonary nodules based on 3D convolution neural network

Published:2018 Issue:5 Volume:26 Page:1211-1218
ISSN:1004-924X
Container-title:Optics and Precision Engineering
language:en
Short-container-title:光学精密工程

Author:

L Xiao-qi 吕晓琪,WU Liang 吴凉,GU Yu 谷宇,ZHANG Wen-li 张文莉,LI Jing 李菁

Publisher

Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences

Subject

Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials

Cited by 19 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Segmentation method of pulmonary nodules based on AC-UNET;Proceedings of the 5th International Conference on Computer Information and Big Data Applications;2024-04-26

2. Bibliometrics researches on the application of artificial intelligence-aided diagnosis system in CT medical diagnosis;Innovation and Emerging Technologies;2024-01

3. ACX-UNet: a multi-scale lung parenchyma segmentation study with improved fusion of skip connection and circular cross-features extraction;Signal, Image and Video Processing;2023-09-28

4. Detection of low‐dose computed tomography pulmonary nodules based on 3D CNN‐CapsNet;Electronics Letters;2023-09

5. RAD-UNet: Research on an improved lung nodule semantic segmentation algorithm based on deep learning;Frontiers in Oncology;2023-03-23

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