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Mining fMRI Dynamics with Parcellation Prior for Brain Disease Diagnosis
Xiaozhao Liu, Mianxin Liu, Lang Mei +4
To characterize atypical brain dynamics under diseases, prevalent studies investigate functional magnetic resonance imaging (fMRI). However, most of the existing analyses compress…
Hierarchical Graph Convolutional Network Built by Multiscale Atlases for Brain Disorder Diagnosis Using Functional Connectivity
Mianxin Liu, Han Zhang, Feng Shi +1
Functional connectivity network (FCN) data from functional magnetic resonance imaging (fMRI) is increasingly used for the diagnoses of brain disorders. However, state-of-the-art st…
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…
Hypergraph Learning for Identification of COVID-19 with CT Imaging
Donglin Di, Feng Shi, Fuhua Yan +12
The coronavirus disease, named COVID-19, has become the largest global public health crisis since it started in early 2020. CT imaging has been used as a complementary tool to assi…
Joint Prediction and Time Estimation of COVID-19 Developing Severe Symptoms using Chest CT Scan
Xiaofeng Zhu, Bin Song, Feng Shi +9
With the rapidly worldwide spread of Coronavirus disease (COVID-19), it is of great importance to conduct early diagnosis of COVID-19 and predict the time that patients might conve…
Adaptive Feature Selection Guided Deep Forest for COVID-19 Classification with Chest CT
Liang Sun, Zhanhao Mo, Fuhua Yan +14
Chest computed tomography (CT) becomes an effective tool to assist the diagnosis of coronavirus disease-19 (COVID-19). Due to the outbreak of COVID-19 worldwide, using the computed…
Diagnosis of Coronavirus Disease 2019 (COVID-19) with Structured Latent Multi-View Representation Learning
Hengyuan Kang, Liming Xia, Fuhua Yan +8
Recently, the outbreak of Coronavirus Disease 2019 (COVID-19) has spread rapidly across the world. Due to the large number of affected patients and heavy labor for doctors, compute…
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…
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…