246 citations · 634 across the 7 of their papers we have counts for
8 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…
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…
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…
Lung Infection Quantification of COVID-19 in CT Images with Deep Learning
Fei Shan, Yaozong Gao, Jun Wang +6
CT imaging is crucial for diagnosis, assessment and staging COVID-19 infection. Follow-up scans every 3-5 days are often recommended for disease progression. It has been reported t…
Large-Scale Screening of COVID-19 from Community Acquired Pneumonia using Infection Size-Aware Classification
Feng Shi, Liming Xia, Fei Shan +7
The worldwide spread of coronavirus disease (COVID-19) has become a threatening risk for global public health. It is of great importance to rapidly and accurately screen patients w…
The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 Challenge
Nicholas Heller, Fabian Isensee, Klaus H. Maier-Hein +38
There is a large body of literature linking anatomic and geometric characteristics of kidney tumors to perioperative and oncologic outcomes. Semantic segmentation of these tumors a…