1k citations · 1k across the 2 of their papers we have counts for
3 papers
eess.IV2020★ 13 cited
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…
eess.IV2020★ 1k cited
Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19
Feng Shi, Jun Wang, Jun Shi +6
(This paper was submitted as an invited paper to IEEE Reviews in Biomedical Engineering on April 6, 2020.) The pandemic of coronavirus disease 2019 (COVID-19) is spreading all over…
eess.IV2020
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…