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20132023
most citedReview of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19

1k citations · 2.8k across the 70 of their papers we have counts for

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Showing 2020Show all

20 papers · 1 filter

cs.CV2020★ 1 cited

TSGCNet: Discriminative Geometric Feature Learning with Two-Stream GraphConvolutional Network for 3D Dental Model Segmentation

Lingming Zhang, Yue Zhao, Deyu Meng +5

The ability to segment teeth precisely from digitized 3D dental models is an essential task in computer-aided orthodontic surgical planning. To date, deep learning based methods ha…

q-bio.NC2020★ 2 cited

Co-evolution of Functional Brain Network at Multiple Scales during Early Infancy

Xuyun Wen, Liming Hsu, Weili Lin +2

The human brains are organized into hierarchically modular networks facilitating efficient and stable information processing and supporting diverse cognitive processes during the c…

cs.CV2020

Deep Modeling of Growth Trajectories for Longitudinal Prediction of Missing Infant Cortical Surfaces

Peirong Liu, Zhengwang Wu, Gang Li +2

Charting cortical growth trajectories is of paramount importance for understanding brain development. However, such analysis necessitates the collection of longitudinal data, which…

cs.LG2020

Learning-based Computer-aided Prescription Model for Parkinson's Disease: A Data-driven Perspective

Yinghuan Shi, Wanqi Yang, Kim-Han Thung +5

In this paper, we study a novel problem: "automatic prescription recommendation for PD patients." To realize this goal, we first build a dataset by collecting 1) symptoms of PD pat…

eess.IV2020★ 110 cited

Multi-Site Infant Brain Segmentation Algorithms: The iSeg-2019 Challenge

Yue Sun, Kun Gao, Zhengwang Wu +30

To better understand early brain growth patterns in health and disorder, it is critical to accurately segment infant brain magnetic resonance (MR) images into white matter (WM), gr…

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…