Prediction and Detection of Covid-19 through Deep Learning Technique |
Author(s): |
Dr.G.Karpagarajesh , Government College of Engineering,Tirunelveli; R.Aarthi, Government College of Engineering,Tirunelveli; C.Arockia Yashini Charles, Government College of Engineering,Tirunelveli; P.Blessy Stejil, Government College of Engineering,Tirunelveli; I.Kulasi Poongothai, Government College of Engineering,Tirunelveli |
Keywords: |
COVID-19, CT Scan Images, Deep Learning, Convolutional Neural Network |
Abstract |
Coronavirus Disease (COVID19) is a rapidly spreading infectious disease which is producing a global healthcare crisis. Due to the present limitations of reverse transcription-polymerase chain reaction (RT-PCR)-based assays for identifying COVID19, numerous works have recently offered radiological imaging-based solutions. Computed Tomography (CT) imaging is useful for detecting COVID-19-related pulmonary symptoms in which segmentation of infection lesions from CT images is important for quantitative evaluation of disease progression and follow-up assessment. For this experimentation, 200 COVID-19 positive lung CT images and 200 COVID-19 negative lung CT images were collected. For validation, 110 images were obtained. The machine is made to learn the attributes of COVID-19 positive and COVID-19 negative images and is made to discriminate those using convolutional neural networks. As a result, when a new CT image is shown, the system will be able to anticipate whether the image is COVID-19 positive or negative. |
Other Details |
Paper ID: IJSRDV10I40352 Published in: Volume : 10, Issue : 4 Publication Date: 01/07/2022 Page(s): 200-205 |
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