COVID-19 Diagnosis with HRCT Images Using Deep Transfer Learning

High-resolution computed tomography (HRCT) is a way of diagnosing, in which x-rays are used to acquire the high resolution images. It is one of the types of Computed Tomography(CT) which is more clear and accurate in giving precise results. The HRCT scan covers the whole lung tissue which helps to find the cause of any abnormalities in scanned images. The present study is undertaken to investigate COVID-19 disease on HRCT images with Deep Transfer Learning models. In this paper, we are proposing Deep Learning model on HRCT Images for predicting whether a patient is affected or not. The Proposed model is an automatic classification of images by considering Mobile Net, Inception Net, VGG16, Resnet50, CNN deep learning models. The results are obtained from Inception Net with classification mean accuracy of 99%. Our model demonstrates the use of InceptionNet deep transfer learning model for diagnosing Covid-19 as an alternate way of testing the infection.