Deep convolutional neural networks for detection of abnormalities in chest X-rays trained on the very large dataset-Reference-Cited by-同舟云学术

Deep convolutional neural networks for detection of abnormalities in chest X-rays trained on the very large dataset

Published:2022-07-20 Issue:4 Volume:17 Page:1035-1041
ISSN:1863-1703
Container-title:Signal, Image and Video Processing
language:en
Short-container-title:SIViP

Author:

Aktas Kadir^ORCID,Ignjatovic Vuk,Ilic Dragan,Marjanovic Marina,Anbarjafari Gholamreza

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Signal Processing

Link

https://link.springer.com/content/pdf/10.1007/s11760-022-02309-w.pdf

Reference33 articles.

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3. Chan, J.F.-W., Yuan, S., Kok, K.-H., To, K.K.-W., Chu, H., Yang, J., Xing, F., Liu, J., Yip, C.C.-Y., Poon, R.W.-S., et al.: A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet 395(10223), 514–523 (2020)

4. Zhao, W., Zhong, Z., Xie, X., Yu, Q., Liu, J.: Relation between chest ct findings and clinical conditions of coronavirus disease (Covid-19) pneumonia: a multicenter study. Am. J. Roentgenol. 214(5), 1072–1077 (2020)

5. Hemdan, E.E.D., Shouman, M.A., Karar, M.E.: Covidx-net: a framework of deep learning classifiers to diagnose Covid-19 in X-ray images. arXiv preprint arXiv:2003.11055 (2020)

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