利用深度学习从胸部x线图像中检测COVID-19

I. Bellamine, Hakim Nasaoui, H. Silkan
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摘要

COVID-19是由最后发现的冠状病毒引起的传染病。在2019年12月中国武汉爆发疫情之前,这种新的病毒和疾病是未知的。COVID-19目前已成为大流行,影响到世界许多国家。由于COVID-19是一种流感,因此可以使用放射成像技术进行诊断。随着深度学习领域的快速发展,已经出现了对正常人、肺炎和COVID-19患者进行分类的智能系统。在这项研究中,我们提出了一个新的神经网络,它是VGG16, ResNet-50和exception网络的连接。所提出的网络对所有类别的总体平均准确率为98%,检测COVID-19病例的平均准确率为100%。
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Detection of COVID-19 from Chest X-ray images using Deep learning
COVID-19 is the infectious disease caused by the last corona virus that was discovered. This new virus and disease was unknown before the outbreak in Wuhan, China, in December 2019. COVID-19 is now pandemic and affects many countries around the world. Since COVID-19 is a type of flu, it can be diagnosed using radiology imaging techniques. With rapid development in the field of deep learning, there had been intelligent systems to classify between normal, pneumonia and COVID-19 patients. In this study, we have proposed a new neural network that is a concatenation of VGG16, ResNet-50 and Xception networks. The overall average accuracy of the proposed network for all classes is 98%, and the average accuracy for detecting COVID-19 cases is 100%.
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