利用深度学习技术从胸部x光片中检测COVID-19

T. A. Suresh, Viji Rajendran V
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摘要

世界卫生组织(世卫组织)于2020年3月宣布,冠状病毒病(COVID-19)是一种全球大流行。医学图像分析是一种众所周知的检测新冠病毒的方法。这是因为心血管系统是受病毒影响最大的人体器官,因此胸部x光检查可能比热筛查更合适。深度学习(DL)算法可以在COVID-19患者的胸部x光片(CXR)诊断中发挥关键作用,只要对其进行适当的研究。covid检测的第一阶段是预处理,即裁剪和调整图像大小以进行快速处理。下一步是利用深度卷积网络进行特征提取和分类。研究了各阶段涉及的各种方法,并利用预训练模型建立了模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
COVID-19 Detection from Chest X-Rays Using Deep Learning Techniques
The CoronaVirus Disease (COVID-19) is a global pandemic, according to theWorld Health Organization (WHO), which was declared in March 2020. Medical image analysis is a well-known method that could be useful in detecting COVID-19. This is because the cardiovascular system is the organ in the body that is most affected by the virus, so the chest X-rays may be a more suitable technique than thermal screening. Deep learning (DL) algorithms can play a crucial role in diagnosing COVID-19 patients’ Chest X-Ray (CXR) pictures when properly studying them. The first stage involved in covid detection is pre-processing where cropping and resizing of image for fast processing. The next stage is feature extraction and classification by using deep convolution network. Various methods involved in these stages are studied and model was build using Pre-trained models.
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