论文标题
Covidx：Covid-19的计算机辅助诊断及其用原始数字胸部X射线图像预测的严重性预测
COVIDX: Computer-aided diagnosis of Covid-19 and its severity prediction with raw digital chest X-ray images
论文作者
论文摘要
冠状病毒病（Covid-19）是由严重的急性呼吸道综合征-2（SARS-COV-2）引起的一种传染性感染，它已感染并杀死了全球数百万的人。在没有特定药物或疫苗以治疗Covid-19和限制的局限性诊断技术的情况下，医生可以使用某些替代自动筛查系统可以快速识别和隔离感染患者。胸部X射线（CXR）图像可以用作检测和诊断COVID-19的替代方式。在这项研究中，我们提出了一种自动Covid-19诊断和严重性预测（COVIDX）系统，该系统使用CXR图像的深度特征图来诊断Covid-19及其严重性预测。拟议的系统使用不同的浅层监督分类算法采用三相分类方法（健康与不健康，COVID-19与肺炎和Covid-19的严重性）。我们不仅通过10倍Cross2验证以及使用外部验证数据集评估了Covidx，还通过涉及经验丰富的放射科医生来评估COVIDX。在所有评估设置中，Covidx优于为此目的而设计的所有现有状态方法。我们可以通过基于云的Web服务器和Python代码轻松访问Covidx，分别在https://sites.google.com/view/wajidarshad/software和https://github.com/wajidarshad/covidx上获得。
Coronavirus disease (COVID-19) is a contagious infection caused by severe acute respiratory syndrome coronavirus-2 (SARS-COV-2) and it has infected and killed millions of people across the globe. In the absence of specific drugs or vaccines for the treatment of COVID-19 and the limitation of prevailing diagnostic techniques, there is a requirement for some alternate automatic screening systems that can be used by the physicians to quickly identify and isolate the infected patients. A chest X-ray (CXR) image can be used as an alternative modality to detect and diagnose the COVID-19. In this study, we present an automatic COVID-19 diagnostic and severity prediction (COVIDX) system that uses deep feature maps from CXR images to diagnose COVID-19 and its severity prediction. The proposed system uses a three-phase classification approach (healthy vs unhealthy, COVID-19 vs Pneumonia, and COVID-19 severity) using different shallow supervised classification algorithms. We evaluated COVIDX not only through 10-fold cross2 validation and by using an external validation dataset but also in real settings by involving an experienced radiologist. In all the evaluation settings, COVIDX outperforms all the existing stateof-the-art methods designed for this purpose. We made COVIDX easily accessible through a cloud-based webserver and python code available at https://sites.google.com/view/wajidarshad/software and https://github.com/wajidarshad/covidx, respectively.
