  Automatic pneumonia Detection based on deep learning has increasing clinical
value. Although the existing Feature Pyramid Network (FPN) and its variants
have already achieved some great successes, their detection accuracies for
pneumonia lesions in medical images are still unsatisfactory. In this paper, we
propose a pneumonia detection network based on feature pyramid attention
enhancement, which integrates attended high-level semantic features with
low-level information. We add another information extracting path equipped with
feature enhancement modules, which are conducted with an attention mechanism.
Experimental results show that our proposed method can achieve much better
performances, as a higher value of 4.02% and 3.19%, than the baselines in
detecting pneumonia lesions.
