Covid-19 and Pneumonia Chest Infection Detection and Classification using Convolutional Neural Networks - Shaurya Choudhary Manjula R Saransh Mehta Pratham Sharma (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
Various machine learning, deep learning and image processing techniques are used frequently in detecting the presence of diseases and infections from medical images. Detecting COVID- 19 and pneumonic infections takes special skills and techniques because they are difficult to detect – especially in early stages. We have developed a web application which incorporates all the functionalities for uploading the chest radiograph input image, perform processing on the input image, perform classification and finally output the predicted disease category, its class probability, and provide an option to download the diagnosis report, generated automatically. The complete system incorporates a convolutional neural network model which performs classification on input mages after performing image processing operations. The convolutional neural network is trained on an extensive dataset of chest radiograph images, covering chest X-ray images of patients affected with pneumonia and COVID- 19 as well as normal chest X-rays. This classification model was able to achieve a great accuracy and precision.