Using Deep Learning to Locate Lung Tumor from Chest X-ray Images

Pneumonia is one of the top ten causes of death. Early diagnosis of pneumonia is essential for subsequent effective treatment. Judging from the current development situation, many effective artificial intelligence (AI) algorithms are concentrated on diseases with a large amount of standardized data. After all, to achieve high-quality AI diagnosis, a large number of high-quality annotated images are required for pre-algorithm training.This research uses semi-supervised learning with Tensorflow and keras two frameworks to construct a disease location system. We use VGG16 and establish a deep convolutional generation confrontation network (DCGAN) [1], synthesize chest X-ray data, and amplify the data set. With an improved visualization effect, a heat map is used to display the lesions to assist clinical medical care personnel to fully grasp the patient's condition. We show examples of CAMs on the pneumonia detection task with no augmentation and DCGAN. It can be concluded that DCGAN performs the best results, the accuracy rate was increased by 11%.