泰经纪人莫拉比托-的A2,弗朗西斯科·卡罗盟-塔希尔,所有非盟- Haweel雷姆t . AU - Al Bastaki乌萨马·m·h . AU - Abdelwahed埃曼AU -拉赫曼,塔里克盟——Haweel Tarek i . PY - 2022 DA - 2022/10/20 TI -快速COVID-19检测从胸部x光图像使用DCT压缩SP - 2656818六世- 2022 AB -新型冠状病毒(COVID-19)是一种新型冠状病毒,首次发现在集群SARS-CoV-2病毒引起的肺炎症状。它快速传播世界各地。大多数感染者会出现轻度至中度疾病和恢复无需住院。目前,实时定量一(rqRT-PCR)是受欢迎的冠状病毒检测由于其高特异性、简单的定量分析,比传统的rt - pcr和更高的灵敏度。抗原测试也被广泛使用。这是非常基本的自动检测COVID-19公开可用的资源。胸部x光片(CXR)图像用于COVID-19的分类,正常,病毒性肺炎病例。CXR分为图像子块寻找出每个子块的离散余弦变换(DCT)的方法。为了产生一个为每个CXR图像压缩版本,使用DCT的能量压缩功能。对于每一个图像,几乎没有几个光谱DCT组件作为特征。 The dimension of the final feature vectors is reduced by scanning the compressed images using average pooling windows. In the 3-set classification, a multilayer artificial neural network is used. It is essential to triage non-COVID-19 patients with pneumonia to give out hospital resources efficiently. Higher size feature vectors are used for designing binary classification for COVID-19 and pneumonia. The proposed method achieved an average accuracy of 95% and 94% for the 3-set classification and binary classification, respectively. The proposed method achieves better accuracy than that of the recent state-of-the-art techniques. Also, the time required for the implementation is less. SN - 1687-9724 UR - https://doi.org/10.1155/2022/2656818 DO - 10.1155/2022/2656818 JF - Applied Computational Intelligence and Soft Computing PB - Hindawi KW - ER -