Abstract:
Streptococcus pneumoniae bacteria can cause life-threatening pneumonia in humans. WHO reports that pneumonia kills one in three Indians. Expert radiotherapists evaluate pneumonia-diagnosing chest X-rays. In remote areas, an automatic pneumonia detection system would help treat the disease quickly.
Deep learning algorithms’ success in analyzing medical images has made Convolutional Neural Networks (CNNs) popular for disease classification. Pre-trained CNN models on large datasets also help image classification.
We evaluate pre-trained CNN models as feature-extractors and different classifiers for classifying abnormal and normal chest X-Rays. We analyze the best CNN model. Statistics show that pretrained CNN models and supervised classifier algorithms can help detect pneumonia in chest X-ray images.
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