Open AccessDiagnosis of COVID-19 Infected Lungs from Chest X-Ray Images
Author(s) -
T. S. R. Niloy,
Akm Fazlur Rahman
Publication year - 2021
Publication title -
the aiub journal of science and engineering
Language(s) - English
Resource type - Journals
eISSN - 2520-4890
pISSN - 1608-3679
DOI - 10.53799/ajse.v20i1.142
Subject(s) - covid-19 , coronavirus , pneumonia , medicine , etiology , convolutional neural network , virus , disease , virology , pathology , artificial intelligence , computer science , infectious disease (medical specialty)
Severe Acute Respiratory Symptom Coronavirus 2 (SARS-CoV-2) was newly discovered as a beta coronavirus. The virus-induced unexplained etiological pneumonia and is referred to as the 2019 Coronavirus Disease (COVID-19). Though the disease has appeared in a new way, there is no medication for transited patients. So, for diagnosing the COVID-19 infected lungs from X-Ray images, an automated technique has been suggested in this manuscript. In this study, Convolutional neural network (CNN) and VGG19 were used and found accuracy scores of 97% and 67%, respectively. The comparative analysis shows that the proposed method performs better than the solution that exists. Eventually, Precision, Recall, and F1-Score have been extracted and interpreted the model's loss functions in the research. This research has carried out by focusing on essential aspects in terms of COVID-19. Therefore, for the diagnosis of coronavirus infection, the technique can be used effectively.