Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Weakly Supervised Lesion Localization With Probabilistic-CAM Pooling   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. PCAM pooling explicitly leverages the excellent localization
ability of CAM during training in a probabilistic fashion. Experiments on the
ChestX-ray14 dataset show a ResNet-34 model trained with PCAM pooling
outperforms state-of-the-art baselines on both the classification task and the
localization task. Visual examination on the probability maps generated by PCAM
pooling shows clear and sharp boundaries around lesion regions compared to the
localization heatmaps generated by CAM. PCAM pooling is open sourced at
https://github.com/jfhealthcare/Chexpert.

36
The categories of this paper are: cmp-lg
12
The categories of this paper are: nucl-th
8
The categories of this paper are: hep-ex
25
The categories of this paper are: patt-sol
9
The categories of this paper are: nlin
7
The categories of this paper are: hep-th
10
The categories of this paper are: q-bio
17
The categories of this paper are: q-fin
32
The categories of this paper are: atom-ph
5
The categories of this paper are: gr-qc
2
The categories of this paper are: math
34
The categories of this paper are: chem-ph
30
The categories of this paper are: q-alg
21
The categories of this paper are: adap-org
13
The categories of this paper are: quant-ph
27
The categories of this paper are: comp-gas