149 citations · 226 across the 5 of their papers we have counts for
5 papers
Cross-Site Severity Assessment of COVID-19 from CT Images via Domain Adaptation
Geng-Xin Xu, Chen Liu, Jun Liu +9
Early and accurate severity assessment of Coronavirus disease 2019 (COVID-19) based on computed tomography (CT) images offers a great help to the estimation of intensive care unit…
A novel multiple instance learning framework for COVID-19 severity assessment via data augmentation and self-supervised learning
Zekun Li, Wei Zhao, Feng Shi +9
How to fast and accurately assess the severity level of COVID-19 is an essential problem, when millions of people are suffering from the pandemic around the world. Currently, the c…
Synergistic Learning of Lung Lobe Segmentation and Hierarchical Multi-Instance Classification for Automated Severity Assessment of COVID-19 in CT Images
Kelei He, Wei Zhao, Xingzhi Xie +8
Understanding chest CT imaging of the coronavirus disease 2019 (COVID-19) will help detect infections early and assess the disease progression. Especially, automated severity asses…
Dual-Sampling Attention Network for Diagnosis of COVID-19 from Community Acquired Pneumonia
Xi Ouyang, Jiayu Huo, Liming Xia +15
The coronavirus disease (COVID-19) is rapidly spreading all over the world, and has infected more than 1,436,000 people in more than 200 countries and territories as of April 9, 20…
Severity Assessment of Coronavirus Disease 2019 (COVID-19) Using Quantitative Features from Chest CT Images
Zhenyu Tang, Wei Zhao, Xingzhi Xie +4
Background: Chest computed tomography (CT) is recognized as an important tool for COVID-19 severity assessment. As the number of affected patients increase rapidly, manual severity…