Detection of Covid-19 Severity with CT Scan Images using Segmentation Techniques

Prakash. J, Haham Debbarma, Ramraj Ram Vardhan, Arunit Baidya, Karthik Anand, P Prudhvi Sai

2022 6th International Conference on Trends in Electronics and Informatics (ICOEI)(2022)

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摘要
The impact of COVID-19 is severe worldwide; detecting the Covid severity in a patient is a vital step. The further important actions such as isolating the patient from others and testing the people in frequent contact with the patient can only be done after the Covid-19 test results. Currently, different methods are used for detecting the Corona virus in a patient, they are Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) test, Rapid Diagnostic Test (RDT), and Computed Tomography (CT) scan for lungs. However, a CT scan is the most accurate way to detect covid compared to other tests. The CT scan can produce images of the lungs within 15 to 20 minutes. Whereas traditional methods such as RT-PCR will take at least six to eight hours to deliver results. This paper aims to determine the severity level of Covid from the Computed Tomography (CT) scan image of the lungs
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关键词
COVID-19,RT-PCR,Computed Tomography (CT) Scan,CT Severity score,Ground Glass Opacities (GGO),Superpixel Segmentation,Lobes,Contours
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