Attention-Guided Curriculum Learning for Weakly Supervised Classification and Localization of Thoracic Diseases on Chest Radiographs

Bengio, Y., Louradour, J., et al.: Curriculum learning. In: ICML (2009)

2009

Earlier work this paper cites.

Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. In: NIPS (2012)

2012

Earlier work this paper cites.

He, K., et al.: Deep residual learning for image recognition. In: IEEE CVPR (2016)

2016

Earlier work this paper cites.

Shi, M., Ferrari, V.: Weakly supervised object localization using size estimates. In: ECCV (2016)

2016

Earlier work this paper cites.

Tang, Y., Wang, J., Gao, B., et al.: Large scale semi-supervised object detection using visual and semantic knowledge transfer. In: IEEE CVPR (2016)

2016

Earlier work this paper cites.

Zhou, B., Khosla, A., Lapedriza, A., Oliva, A., Torralba, A.: Learning deep features for discriminative localization. In: IEEE CVPR (2016)

2016

Cited alongside, same era.

Lakhani, P., Sundaram, B.: Deep learning at chest radiography: Automated classification of pulmonary tuberculosis by using convolutional neural networks. Radiology 284(2) (2017)

2017

Cited alongside, same era.

Rajpurkar, P., Irvin, J., Zhu, K., Yang, B., et al.: Chexnet: Radiologist-level pneumonia detection on chest x-rays with deep learning. arXiv: 1711.05225 (2017)

2017

Cited alongside, same era.

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

2017

Cited alongside, same era.

Jin, D., Xu, Z., et al.: CT-realistic lung nodule simulation from 3D conditional generative adversarial networks for robust lung segmentation. In: MICCAI (2018)

Li, Z., Wang, C., Han, M., Xue, Y., Wei, W., Li, L.J., Fei-Fei, L.: Thoracic disease identification and localization with limited supervision. In: IEEE CVPR (2018)

2018

Closest in time.

Tang, Y., et al.: Semi-automatic RECIST labeling on CT scans with cascaded convolutional neural networks. In: MICCAI (2018)

2018

Closest in time.

Wang, X., Peng, Y., et al.: Tienet: Text-image embedding network for common thorax disease classification and reporting in chest x-rays. In: IEEE CVPR (2018)

2018

Closest in time.

Yan, K., et al.: Deeplesion: automated mining of large-scale lesion annotations and universal lesion detection with deep learning. J. Med. Imag. 5(3) (2018)

2018

Closest in time.