Pneumonia is a common disease that affects mil-lions of people globally, typically requiring the expertise of experienced radiologists to diagnose the disease. Previous methods learn to detect pneumonia through comparison of global spatial features of other diseases. Our proposed pneumonia detection method uses the identification of regions of interest within chestX-ray images and then performs classification of the regions.Experiment results show that our two-stage object detection and classification can achieve higher recall and accuracy.