  COVID-19 (Coronavirus disease 2019) has been quickly spreading since its
outbreak, impacting financial markets and healthcare systems globally.
Countries all around the world have adopted a number of extraordinary steps to
restrict the spreading virus, where early COVID-19 diagnosis is essential.
Medical images such as X-ray images and Computed Tomography scans are becoming
one of the main diagnostic tools to combat COVID-19 with the aid of deep
learning-based systems. In this survey, we investigate the main contributions
of deep learning applications using medical images in fighting against COVID-19
from the aspects of image classification, lesion localization, and severity
quantification, and review different deep learning architectures and some image
preprocessing techniques for achieving a preciser diagnosis. We also provide a
summary of the X-ray and CT image datasets used in various studies for COVID-19
detection. The key difficulties and potential applications of deep learning in
fighting against COVID-19 are finally discussed. This work summarizes the
latest methods of deep learning using medical images to diagnose COVID-19,
highlighting the challenges and inspiring more studies to keep utilizing the
advantages of deep learning to combat COVID-19.
