Symmetry-Aware Siamese Network: Exploiting Pathological Asymmetry for Chest X-Ray Analysis-Reference-Cited by-同舟云学术

Symmetry-Aware Siamese Network: Exploiting Pathological Asymmetry for Chest X-Ray Analysis

Published:2023 Issue: Volume: Page:165-176
ISSN:0302-9743
Container-title:Artificial Neural Networks and Machine Learning – ICANN 2023
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Author:

Schneider Helen,Yildiz Elif Cansu,Biesner David,Layer Yannik C.,Wulff Benjamin,Nowak Sebastian,Theis Maike,Sprinkart Alois M.,Attenberger Ulrike I.,Sifa Rafet

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-44216-2_14

Reference25 articles.

1. Nabulsi, Z., et al.: Deep learning for distinguishing normal versus abnormal chest radiographs and generalization to two unseen diseases tuberculosis and COVID-19. Sci. Rep. 11(1) (2021)

2. Stevens, B.J., et al.: Radiographers reporting chest x-ray images: identifying the service enablers and challenges in England, UK. Radiography 27(4), 1006–1013 (2021)

3. Schneider, H., et al.: Towards symmetry-aware pneumonia detection on chest x-rays. In: 2022 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 543–550 (2022)

4. Irvin, J., Rajpurkar, P., et al.: Chexpert: a large chest radiograph dataset with uncertainty labels and expert comparison (2019)

5. Pham, H.H., et al.: Interpreting chest x-rays via CNNs that exploit hierarchical disease dependencies and uncertainty labels. Neurocomputing 437, 186–194 (2021)

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