Detection of Covid-19 on Localized Ct-scan Images Using Deep Learning Convolution Neural Network

Abstract

Pneumonia Coronavirus Disease 2019 (COVID-19) is an inflammation of the lung parenchyma caused by Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Supporting examinations carried out to establish a diagnosis of Covid-19 is through radiological examinations, one of which is Computed Tomography Scan (CT-Scan). The current method used to diagnose COVID-19 from CT scan images is by studying the 2-D CT Scan image data set using naked eye, then interpreting the data one by one. This procedure is ineffective. Research aim is to develop Covid-19 detection application on localized CT-Scan images using Deep Learning Convolution Neural Network (CNN). Pre-Trained Model used is ResNet-50. Test was carried out 3 times. First test uses original CT image, with an accuracy of 92.5%. Second test used pulmonary CT data that had been separated from surrounding tissue, with an accuracy of 95%. The last test used localized CT data (Covid Candidate), the accuracy obtained was 98%.