论文标题
COVIDX CXR-3：用于计算机辅助COVID-19诊断的大型，开源基准X射线图像
COVIDx CXR-3: A Large-Scale, Open-Source Benchmark Dataset of Chest X-ray Images for Computer-Aided COVID-19 Diagnostics
论文作者
论文摘要
自从Covid-19大流行开始以来已有两年多之后，这场危机的压力继续在全球范围内破坏。将胸部X射线（CXR）成像用作RT-PCR测试的互补筛查策略不仅盛行，而且由于其常规临床用于呼吸疾病，而且大大增加了。迄今为止，已经提出了许多基于CXR成像的COVID-19筛选的视觉感知模型。然而，这些模型的准确性和概括能力在很大程度上取决于训练数据集的多样性和大小。在此激励的情况下，我们引入了Covidx CXR-3，这是CXR图像的大规模基准数据集，用于支持Covid-19的计算机视觉研究。 COVIDX CXR-3由来自至少51个国家 /地区的17,026名患者组成的30,386个CXR图像组成，这使得我们最好，最广泛，最多样化的COVID-19 CXR数据集以开放式访问形式。在这里，我们提供了有关拟议数据集的各个方面的全面详细信息，包括患者人口统计，成像视图和感染类型。希望COVIDX CXR-3可以帮助科学家推进机器学习研究，以防止COVID-19的大流行和相关疾病。
After more than two years since the beginning of the COVID-19 pandemic, the pressure of this crisis continues to devastate globally. The use of chest X-ray (CXR) imaging as a complementary screening strategy to RT-PCR testing is not only prevailing but has greatly increased due to its routine clinical use for respiratory complaints. Thus far, many visual perception models have been proposed for COVID-19 screening based on CXR imaging. Nevertheless, the accuracy and the generalization capacity of these models are very much dependent on the diversity and the size of the dataset they were trained on. Motivated by this, we introduce COVIDx CXR-3, a large-scale benchmark dataset of CXR images for supporting COVID-19 computer vision research. COVIDx CXR-3 is composed of 30,386 CXR images from a multinational cohort of 17,026 patients from at least 51 countries, making it, to the best of our knowledge, the most extensive, most diverse COVID-19 CXR dataset in open access form. Here, we provide comprehensive details on the various aspects of the proposed dataset including patient demographics, imaging views, and infection types. The hope is that COVIDx CXR-3 can assist scientists in advancing machine learning research against both the COVID-19 pandemic and related diseases.
