A review of Deep learning Techniques for COVID-19 identification on Chest CT images
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by
Briskline Kiruba S, Petchiammal A, D. Murugan
2022
Abstract
The current COVID-19 pandemic is a serious threat to humanity that directly
affects the lungs. Automatic identification of COVID-19 is a challenge for
health care officials. The standard gold method for diagnosing COVID-19 is
Reverse Transcription Polymerase Chain Reaction (RT-PCR) to collect swabs from
affected people. Some limitations encountered while collecting swabs are
related to accuracy and longtime duration. Chest CT (Computed Tomography) is
another test method that helps healthcare providers quickly identify the
infected lung areas. It was used as a supporting tool for identifying COVID-19
in an earlier stage. With the help of deep learning, the CT imaging
characteristics of COVID-19. Researchers have proven it to be highly effective
for COVID-19 CT image classification. In this study, we review the recent deep
learning techniques that can use to detect the COVID-19 disease. Relevant
studies were collected by various databases such as Web of Science, Google
Scholar, and PubMed. Finally, we compare the results of different deep learning
models, and CT image analysis is discussed.
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