COVD-19 Detection Platform from X-ray Images using Deep Learning

M. Elbes, Tarek Kanan, Mohammad Alia, Mohammad Ziad
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引用次数: 1

Abstract

Abstract Since the early days of 2020, COVID-19 has tragic effects on the lives of human beings all over the world. To combat this disease, it is important to survey the infected patients in an inexpensive and fast way. One of the most common ways of achieving this is by performing radiological testing using chest X-Rays and patient coughing sounds. In this work, we propose a Convolutional Neural Network-based solution which is able to identify the positive COVID-19 patients using chest XRay images. Multiple CNN models have been adopted in our work. Each of these models provides a decision whether the patient is affected with COVID-19 or not. Then, a weighted average selection technique is used to provide the final decision. To test the efficiency of our model we have used publicly available chest X-ray images of COVID positive and negative cases. Our approach provided a classification performance of 88.5%. Keywords: COVID-19, CT-Images, Deep Learning, CNN Algorithm.
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使用深度学习从X射线图像中检测新冠肺炎的平台
摘要自2020年初以来,新冠肺炎给世界各地的人类生活带来了悲惨的影响。为了对抗这种疾病,以一种廉价而快速的方式对感染患者进行调查是很重要的。实现这一点的最常见方法之一是使用胸部X射线和患者咳嗽声进行放射学测试。在这项工作中,我们提出了一种基于卷积神经网络的解决方案,该解决方案能够使用胸部XRay图像识别新冠肺炎阳性患者。在我们的工作中采用了多种CNN模型。这些模型中的每一个都提供了患者是否受新冠肺炎影响的决定。然后,使用加权平均选择技术来提供最终决策。为了测试我们模型的效率,我们使用了公开的新冠肺炎阳性和阴性病例的胸部X光图像。我们的方法提供了88.5%的分类性能。关键词:新冠肺炎,CT图像,深度学习,CNN算法。
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来源期刊
International Journal of Advances in Soft Computing and its Applications
International Journal of Advances in Soft Computing and its Applications Computer Science-Computer Science Applications
CiteScore
3.30
自引率
0.00%
发文量
31
期刊介绍: The aim of this journal is to provide a lively forum for the communication of original research papers and timely review articles on Advances in Soft Computing and Its Applications. IJASCA will publish only articles of the highest quality. Submissions will be evaluated on their originality and significance. IJASCA invites submissions in all areas of Soft Computing and Its Applications. The scope of the journal includes, but is not limited to: √ Soft Computing Fundamental and Optimization √ Soft Computing for Big Data Era √ GPU Computing for Machine Learning √ Soft Computing Modeling for Perception and Spiritual Intelligence √ Soft Computing and Agents Technology √ Soft Computing in Computer Graphics √ Soft Computing and Pattern Recognition √ Soft Computing in Biomimetic Pattern Recognition √ Data mining for Social Network Data √ Spatial Data Mining & Information Retrieval √ Intelligent Software Agent Systems and Architectures √ Advanced Soft Computing and Multi-Objective Evolutionary Computation √ Perception-Based Intelligent Decision Systems √ Spiritual-Based Intelligent Systems √ Soft Computing in Industry ApplicationsOther issues related to the Advances of Soft Computing in various applications.
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