COVID-19 Detection using Chest X-RAY

Jai Shankar K. N., P. G. R., N. C K
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Abstract

In view of the COVID-19 pandemic, the exponential increase in the COVID-19 patients is leading to the enormous demand on the healthcare systems across the world. The allocation of resources towards the detection of the people affected by the virus plays a key role in curbing the pandemic and slowing down the spread of the virus to a greater extent. While traditional procedures are utilized to discover COVID-19 individuals, testing each individual with a limited number of testing kits is a massive undertaking. Most healthcare systems include X-ray equipment, and most of them being digitized, can be utilized as a way of screening for COVID-19 patients. This paper proposes AI model that can analyze and predict a possible COVID-19 patient, which can be used to prioritize the people for further testing. Further we propose the automation of this process where the models can be deployed in a remote server or an edge computing device where the X-ray images can be screened by the deep learning model to give predictions with very less turnaround time.
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胸部x线检测COVID-19
鉴于COVID-19大流行,COVID-19患者呈指数级增长,导致世界各地对医疗保健系统的需求巨大。分配资源用于检测受病毒影响的人,在遏制大流行和更大程度上减缓病毒传播方面发挥着关键作用。虽然传统程序用于发现COVID-19个体,但使用有限数量的检测试剂盒对每个个体进行检测是一项艰巨的任务。大多数医疗保健系统都有x光设备,其中大部分都是数字化的,可以用作筛查COVID-19患者的一种方式。本文提出了一种人工智能模型,该模型可以分析和预测可能的COVID-19患者,并可用于优先考虑进一步检测的人群。此外,我们建议将该过程自动化,其中模型可以部署在远程服务器或边缘计算设备中,其中x射线图像可以通过深度学习模型进行筛选,以非常少的周转时间给出预测。
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来源期刊
International Journal of Circuits, Systems and Signal Processing
International Journal of Circuits, Systems and Signal Processing Engineering-Electrical and Electronic Engineering
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