Pneumonia Detection in Chest X-rays using CNN

Abstract

Pneumonia is a life-threatening condition which affects people of all ages but is mostly found in infants and older adults. It is caused by a variety of factors including bacteria, viruses and fungi and causes infections in one lung or both. The diagnosis of Pneumonia is usually facilitated using chest X-rays. This diagnosis becomes difficult in cases where access to expert radiologists or doctors to discover the disease is unavailable. Hence, using a system which makes use of powerful Machine Learning and Deep Learning techniques in order to make the diagnosis of Pneumonia in chest X-rays easier is more feasible. This problem has seen tremendous advancements in recent times with the use of various Computer Vision and ML methodologies. In this work, we have showcased the use of multiple such methods in order to create a complete system based on the purpose of detecting Pneumonia in chest X-rays. The integral component of the system is a Convolutional Neural Network (CNN) model, trained on a pre-processed dataset of chest X-rays. CNN has become the most used Deep Learning algorithm for computer vision problems due to its strength of dealing with images.