An Empirical Study of Pre-Trained CNN Models on COVID-19 CT Scan Images

As COVID-19 is highly infectious, the prevention of this disease is mandatory. The instant diagnosis of this disease is obligatory to stop the infection. The most commonly used procedure for COVID-19 detection is the RT-PCR test. But this process is very time-consuming and as a result, it allows the covid infected persons to spread the infection before they come to know the test result. So, in this paper, we used the method of detecting COVID-19 from CT scan images as a replacement for the conventional RT-PCR test. But this alternative method has its demerit too. To diagnose COVID-19 from these CT scan images, the analysis of a radiologist expert is required. So, we have used a deep-learning based method for automatic detection of covid infection from the CT scan images. We have used six pre-trained models: ResNet50, Xception, DenseNet121, DenseNet201, MobileNet, MobileNetV2 and their accuracy are 97.38%, 92.35%, 95.56%, 93.55%, 93.95%, and 92.94% respectively.