  Pneumothorax is a relatively common disease, but in some cases, it may be
difficult to find with chest radiography. In this paper, we propose a novel
method of detecting pneumothorax in chest radiography. We propose an ensemble
model of identical convolutional neural networks (CNN) with three different
sizes of radiography images. Conventional methods may not properly characterize
lost features while resizing large size images into 256 x 256 or 224 x 224
sizes. Our model is evaluated with ChestX-ray dataset which contains over
100,000 chest radiography images. As a result of the experiment, the proposed
model showed AUC 0.911, which is the state of the art result in pneumothorax
detection. Our method is expected to be effective when applying CNN to large
size medical images.
