A deep-learning-based framework for identifying and localizing multiple abnormalities and assessing...
A deep-learning-based framework for identifying and localizing multiple abnormalities and assessing cardiomegaly in chest X-ray
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Author / Creator
Fan, Weijie , Yang, Yi , Qi, Jing , Zhang, Qichuan , Liao, Cuiwei , Wen, Li , Wang, Shuang , Wang, Guangxian , Xia, Yu , Wu, Qihua , Fan, Xiaotao , Chen, Xingcai , He, Mi , Xiao, JingJing , Yang, Liu , Liu, Yun , Chen, Jia , Wang, Bing , Zhang, Lei , Yang, Liuqing , Gan, Hui , Zhang, Shushu , Liu, Guofang , Ge, Xiaodong , Cai, Yuanqing , Zhao, Gang , Zhang, Xi , Xie, Mingxun , Xu, Huilin , Zhang, Yi , Chen, Jiao , Li, Jun , Han, Shuang , Mu, Ke , Xiao, Shilin , Xiong, Tingwei , Nian, Yongjian and Zhang, Dong
Publisher
London: Nature Publishing Group UK
Journal title
Language
English
Formats
Publication information
Publisher
London: Nature Publishing Group UK
Subjects
More information
Scope and Contents
Contents
Accurate identification and localization of multiple abnormalities are crucial steps in the interpretation of chest X-rays (CXRs); however, the lack of a large CXR dataset with bounding boxes severely constrains accurate localization research based on deep learning. We created a large CXR dataset named CXR-AL14, containing 165,988 CXRs and 253,844...
Alternative Titles
Full title
A deep-learning-based framework for identifying and localizing multiple abnormalities and assessing cardiomegaly in chest X-ray
Authors, Artists and Contributors
Author / Creator
Yang, Yi
Qi, Jing
Zhang, Qichuan
Liao, Cuiwei
Wen, Li
Wang, Shuang
Wang, Guangxian
Xia, Yu
Wu, Qihua
Fan, Xiaotao
Chen, Xingcai
He, Mi
Xiao, JingJing
Yang, Liu
Liu, Yun
Chen, Jia
Wang, Bing
Zhang, Lei
Yang, Liuqing
Gan, Hui
Zhang, Shushu
Liu, Guofang
Ge, Xiaodong
Cai, Yuanqing
Zhao, Gang
Zhang, Xi
Xie, Mingxun
Xu, Huilin
Zhang, Yi
Chen, Jiao
Li, Jun
Han, Shuang
Mu, Ke
Xiao, Shilin
Xiong, Tingwei
Nian, Yongjian
Zhang, Dong
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_68ef7730f82e4c09bb080c2475258a52
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_68ef7730f82e4c09bb080c2475258a52
Other Identifiers
ISSN
2041-1723
E-ISSN
2041-1723
DOI
10.1038/s41467-024-45599-z
