Abstract

The world is still overwhelmed by the spread of COVID-19 virus. With total 118,154,964 infected cases as of ninth of March, 2021 and affecting 219 countries and territories, the world is still in the pandemic. The detection of COVID-19 using deep learning method on CT scan images can play vital role in assisting the medical professionals in current pandemic times. To control the spread of disease as well as to support the decision-making process faster by medical professionals, contribution to this area of research is crucial. The current method RT-PCR of diagnosing COVID-19 is time consuming and not available universally. The convolution neural network is widely used in the field of large-scale image recognition. This research aims to classify the COVID-19 pneumonia from bacterial pneumonia, mycoplasma pneumonia and healthy lungs on open-source data available. Considering Inception V3 as backbone classification network, this research retrains the Inception V3 to detect the COVID-19 from CT scan images.