Due to the worldwide spread of the COVID-19, efforts to combat the disease have intensified. Among these efforts, the only effective way to prevent further spread to communities and disease progression is to control the spread of the disease, which is done using public vaccination as well as repeated and rapid testing to diagnose and isolate sick people. In this regard, computer systems with the help of medical science can speed up the diagnosis of COVID-19 disease. This paper, proposed a review of the methods used in rapid and automatic detection of COVID-19 using CT scan images. Finally, by presenting a new method based on deep learning, the obtained results compared with the results of widely used algorithms such as VGG-16 and MobileNet.
CITATION STYLE
Pavlov, V. A., Shariaty, F., Orooji, M., & Velichko, E. N. (2022). Application of Deep Learning Techniques for Detection of COVID-19 Using Lung CT Scans: Model Development and Validation. In Springer Proceedings in Physics (Vol. 268, pp. 85–96). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-81119-8_9
Mendeley helps you to discover research relevant for your work.