No abstract

The on-going COVID-19 outbreak made healthcare systems across the globe to be in the edge of the battle. Recent stats indicate that more than 140+ million confirmed cases are diagnosed globally as of April 2021. The cases are increasing day by day. The early and auto diagnosis helps people to be precautious. The proposed work aims to detect COVID-19 patients and Pneumonia patients from X-Rays which is one of the medical imaging modes to analyse the health of patient's lung inflammation. The suitable Convolutional Neural Network Model is selected for the identified dataset. The model detects COVID-19 patients and Pneumonia patients on the real-world dataset of lung X-Ray images. Images are pre-processed and trained for various classifications like Normal, COVID-19 and Pneumonia. After pre-processing, the detection of the disease is done by selecting the appropriate features from the images in each of the datasets. The result indicates that accuracy of detection of COVID vs Normal and COVID vs Pneumonia. Among those two, COVID vs Normal is with better accuracy than COVID vs Pneumonia. This method detects not only COVID or Pneumonia, but also the subtypes of Pneumonia as bacterial or Viral Pneumonia with 80% and 91.46% respectively. The detection of COVID, Bacterial Pneumonia and Viral Pneumonia using the proposed model helps in rapid diagnosis and to distinguish COVID from Pneumonia and its types which facilitates to use appropriate and fast solutions.