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Deep Convolutional Neural Networks for Detecting COVID-19 Using Medical Images: A Survey.

Authors :
Khattab, Rana
Abdelmaksoud, Islam R.
Abdelrazek, Samir
Source :
New Generation Computing; Jun2023, Vol. 41 Issue 2, p343-400, 58p
Publication Year :
2023

Abstract

Coronavirus Disease 2019 (COVID-19), which is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2), surprised the world in December 2019 and has threatened the lives of millions of people. Countries all over the world closed worship places and shops, prevented gatherings, and implemented curfews to stand against the spread of COVID-19. Deep Learning (DL) and Artificial Intelligence (AI) can have a great role in detecting and fighting this disease. Deep learning can be used to detect COVID-19 symptoms and signs from different imaging modalities, such as X-Ray, Computed Tomography (CT), and Ultrasound Images (US). This could help in identifying COVID-19 cases as a first step to curing them. In this paper, we reviewed the research studies conducted from January 2020 to September 2022 about deep learning models that were used in COVID-19 detection. This paper clarified the three most common imaging modalities (X-Ray, CT, and US) in addition to the DL approaches that are used in this detection and compared these approaches. This paper also provided the future directions of this field to fight COVID-19 disease. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02883635
Volume :
41
Issue :
2
Database :
Complementary Index
Journal :
New Generation Computing
Publication Type :
Academic Journal
Accession number :
163870636
Full Text :
https://doi.org/10.1007/s00354-023-00213-6