Classification and Detection of Pneumonia in X-Ray Images Using Deep Learning Techniques
Blida Montalico, Juan Carlos Herrera
Abstract
Nowadays, artificial intelligence is applied in a great variety of fields. As we know there is an enormous quantity of available data that through artificial intelligence helps to make better and faster decisions furthermore efficiently. This research work is focusing in how to use Deep learning based on convolutional neural networks and propose a classification of pneumonia model through X-ray images. This research work is focusing on how to use deep learning based on convolutional neural networks and proposes a model that can classify pneumonia, through X-ray images. We are using our own model called XrayChestNet_v1 and complex models such as VGG16, ResNeXt50_32x4 y GoogLeNet applying transfer learning technique. In this research, we made two experiments, we tried different architectures in each of them. XrayChestNet_v1, has the task to help to classify and detect whether an X-ray shows changes or signs and classify them in two groups depending on results.