Classification of COVID-19 pneumonia from chest CT images based on reconstructed super-resolution images and VGG neural network

摘要

Section II introduces the basic principles and steps of this method. Firstly, the principle and structure of SRGAN and the effect of image enhancement on the COVID-CT-Dataset are studied. Then, the structure of VGG and its application in chest CT image classification are introduced. Section III introduces the classification experiments, results and discussion of COVID-19 and non-COVID-19 using the method proposed in this paper. Section IV summarizes this work.