39 citations · 77 across the 4 of their papers we have counts for
4 papers · 1 filter
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…
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…