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2020

Weakly Supervised Lesion Localization With Probabilistic-CAM Pooling

Ye, Wenwu, Yao, Jin, Xue, Hui et al.

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Localizing thoracic diseases on chest X-ray plays a critical role in clinical practices such as diagnosis and treatment planning.

However, current deep learning based approaches often require strong supervision, e.g.
annotated bounding boxes, for training such systems, which is infeasible to harvest in large-scale.
We present Probabilistic Class Activation Map (PCAM) pooling, a novel global pooling operation for lesion localization with only image-level supervision.

Weakly Supervised Lesion Localization With Probabilistic-CAM Pooling · Around

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From image-level to pixel-level labeling with convolutional networks
P. O. Pinheiro and R. Collobert · 2015
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Learning deep features for discriminative localization
B. Zhou, A. Khosla, A. Lapedriza, A. Oliva, and A. Torralba · 2016
Earlier work this paper cites.
Chestx-ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases
X. Wang, Y. Peng, L. Lu, Z. Lu, M. Bagheri, and R. M. Summers · 2017
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