COVID-19 的检测方法。
Detection Methods of COVID-19.
机构信息
ATMS Lab, Advanced Technologies for Medicine and Signals, ENIS, Sfax University, Sfax, Tunisia.
King Abdulaziz University (KAU), Jeddah, Saudi Arabia.
出版信息
SLAS Technol. 2020 Dec;25(6):566-572. doi: 10.1177/2472630320962002. Epub 2020 Sep 30.
Abstract
Since being first detected in China, coronavirus disease 2019 (COVID-19) has spread rapidly across the world, triggering a global pandemic with no viable cure in sight. As a result, national responses have focused on the effective minimization of the spread. Border control measures and travel restrictions have been implemented in a number of countries to limit the import and export of the virus. The detection of COVID-19 is a key task for physicians. The erroneous results of early laboratory tests and their delays led researchers to focus on different options. Information obtained from computed tomography (CT) and radiological images is important for clinical diagnosis. Therefore, it is worth developing a rapid method of detection of viral diseases through the analysis of radiographic images. We propose a novel method of detection of COVID-19. The purpose is to provide clinical decision support to healthcare workers and researchers. The article is to support researchers working on early detection of COVID-19 as well as similar viral diseases.
摘要
自在中国首次检测到以来，2019 年冠状病毒病（COVID-19）已在全球迅速传播，引发了一场全球性大流行，目前尚无可行的治愈方法。因此，各国的应对措施侧重于有效遏制其传播。一些国家已经实施了边境管制措施和旅行限制，以限制病毒的进出口。检测 COVID-19 是医生的一项关键任务。早期实验室检测结果有误且存在延迟，这促使研究人员专注于不同的选择。从计算机断层扫描（CT）和放射图像中获取的信息对于临床诊断很重要。因此，值得通过分析放射图像来开发一种快速检测病毒疾病的方法。我们提出了一种检测 COVID-19 的新方法。目的是为医疗保健工作者和研究人员提供临床决策支持。本文旨在为研究 COVID-19 以及类似病毒疾病的早期检测的研究人员提供支持。
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本文引用的文献
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Pattern Anal Appl. 2021;24(3):1207-1220. doi: 10.1007/s10044-021-00984-y. Epub 2021 May 9.
2
A deep learning algorithm using CT images to screen for Corona virus disease (COVID-19).利用 CT 图像进行冠状病毒病（COVID-19）筛查的深度学习算法。
Eur Radiol. 2021 Aug;31(8):6096-6104. doi: 10.1007/s00330-021-07715-1. Epub 2021 Feb 24.
3
COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images.COVID-Net：一种针对胸部 X 光图像中 COVID-19 病例检测的定制化深度卷积神经网络设计。
Sci Rep. 2020 Nov 11;10(1):19549. doi: 10.1038/s41598-020-76550-z.
4
A Deep Learning System to Screen Novel Coronavirus Disease 2019 Pneumonia.一种用于筛查2019冠状病毒病肺炎的深度学习系统。
Engineering (Beijing). 2020 Oct;6(10):1122-1129. doi: 10.1016/j.eng.2020.04.010. Epub 2020 Jun 27.
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6
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