Learning to Recognize Abnormalities in Chest X-Rays with Location-Aware Dense Networks

Author:

Gündel Sebastian,Grbic Sasa,Georgescu Bogdan,Liu Siqi,Maier Andreas,Comaniciu Dorin

Publisher

Springer International Publishing

Reference10 articles.

1. Wang, X., Peng, Y., Lu, L., Lu, Z., Bagheri, M., Summers, R.: Chestx-ray8: hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases. In: Proceedings of CVPR, pp. 3462–3471 (2017)

2. Kamel, S.I., Levin, D.C., Parker, L., Rao, V.M.: Utilization trends in noncardiac thoracic imaging, 2002–2014. JACR 14(3), 337–42 (2017)

3. He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of CVPR, pp. 770–778 (2016)

4. Rajpurkar, P., et al.: CheXNet: radiologist-level pneumonia detection on chest X-rays with deep learning. arXiv:1711.05225 (2017)

5. Yao, L., Poblenz, E., Dagunts, D., Covington, B., Bernard, D., Lyman, K.: Learning to diagnose from scratch by exploiting dependencies among labels. arXiv:1710.10501 (2017)

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