Development and validation of bone-suppressed deep learning classification of COVID-19 presentation in chest radiographs-Reference-Cited by-同舟云学术

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Development and validation of bone-suppressed deep learning classification of COVID-19 presentation in chest radiographs

Published:2022-07 Issue:7 Volume:12 Page:3917-3931
ISSN:2223-4292
Container-title:Quantitative Imaging in Medicine and Surgery
language:
Short-container-title:Quant Imaging Med Surg

Author:

Lam Ngo Fung Daniel,Sun Hongfei,Song Liming,Yang Dongrong,Zhi Shaohua,Ren Ge,Chou Pak Hei,Wan Shiu Bun Nelson,Wong Man Fung Esther,Chan King Kwong,Tsang Hoi Ching Hailey,Kong Feng-Ming Spring,Wáng Yì Xiáng J.,Qin Jing,Chan Lawrence Wing Chi,Ying Michael,Cai Jing

Publisher

AME Publishing Company

Subject

Radiology, Nuclear Medicine and imaging

Link

https://qims.amegroups.com/article/download/95411/pdf

Cited by 3 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. End-to-end deep learning radiomics: development and validation of a novel attention-based aggregate convolutional neural network to distinguish breast diffuse large B-cell lymphoma from breast invasive ductal carcinoma;Quantitative Imaging in Medicine and Surgery;2023-10

2. Deep learning attention-guided radiomics for COVID-19 chest radiograph classification;Quantitative Imaging in Medicine and Surgery;2023-02

3. Artificial intelligence-assisted multistrategy image enhancement of chest X-rays for COVID-19 classification;Quantitative Imaging in Medicine and Surgery;2023-01

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