Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (22): 15-27.DOI: 10.3778/j.issn.1002-8331.2106-0118

• Research Hotspots and Reviews • Previous Articles     Next Articles

COVID-19 Medical Imaging Dataset and Research Progress

LIU Rui, DING Hui, SHANG Yuanyuan, SHAO Zhuhong, LIU Tie   

  1. 1.College of Information Engineering, Capital Normal University, Beijing 100048, China
    2.Beijing Advanced Innovation Center for Image Technology, Beijing 100048, China
    3.Beijing Engineering Research Center of Highly Reliable Embedded System, Beijing 100048, China
    4.Beijing Key Laboratory of Electronic System Reliability Technology, Beijing 100048, China
  • Online:2021-11-15 Published:2021-11-16



  1. 1.首都师范大学 信息工程学院,北京 100048
    2.成像技术北京市高精尖创新中心,北京 100048
    3.高可靠嵌入式系统技术北京市工程研究中心,北京 100048
    4.电子系统可靠性技术北京市重点实验室,北京 100048


As imaging technology has been playing an important role in the diagnosis and evaluation of the new coronavirus(COVID-19), COVID-19 related datasets have been successively published. But few review articles discuss COVID-19 image processing, especially in datasets. To this end, the new coronary pneumonia datasets and deep learning models are sorted and analyzed, through COVID-19-related journal papers, reports, and related open-source dataset websites, which include Computer Tomography(CT) image and X-rays(CXR)image datasets. At the same time, the characteristics of the medical images presented by these datasets are analyzed. This paper focuses on collating and describing open-source datasets related to COVID-19 medical imaging. In addition, some important segmentation and classification models that perform well on the related datasets are analyzed and compared. Finally, this paper discusses the future development trend on lung imaging technology.

Key words: COVID-19 dataset, deep learning, image segmentation, image classification



关键词: COVID-19数据集, 深度学习, 图像分割, 图像分类