1k citations · 1.2k across the 10 of their papers we have counts for
10 papers
One-step Structure Prediction and Screening for Protein-Ligand Complexes using Multi-Task Geometric Deep Learning
Kelei He, Tiejun Dong, Jinhui Wu +1
Understanding the structure of the protein-ligand complex is crucial to drug development. Existing virtual structure measurement and screening methods are dominated by docking and…
Multi-scale Transformer Network with Edge-aware Pre-training for Cross-Modality MR Image Synthesis
Yonghao Li, Tao Zhou, Kelei He +2
Cross-modality magnetic resonance (MR) image synthesis can be used to generate missing modalities from given ones. Existing (supervised learning) methods often require a large numb…
Transformers in Medical Image Analysis: A Review
Kelei He, Chen Gan, Zhuoyuan Li +7
Transformers have dominated the field of natural language processing, and recently impacted the computer vision area. In the field of medical image analysis, Transformers have also…
Cross-Modality Brain Tumor Segmentation via Bidirectional Global-to-Local Unsupervised Domain Adaptation
Kelei He, Wen Ji, Tao Zhou +7
Accurate segmentation of brain tumors from multi-modal Magnetic Resonance (MR) images is essential in brain tumor diagnosis and treatment. However, due to the existence of domain s…
Unsupervised Domain Attention Adaptation Network for Caricature Attribute Recognition
Wen Ji, Kelei He, Jing Huo +2
Caricature attributes provide distinctive facial features to help research in Psychology and Neuroscience. However, unlike the facial photo attribute datasets that have a quantity…
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…
HF-UNet: Learning Hierarchically Inter-Task Relevance in Multi-Task U-Net for Accurate Prostate Segmentation
Kelei He, Chunfeng Lian, Bing Zhang +6
Accurate segmentation of the prostate is a key step in external beam radiation therapy treatments. In this paper, we tackle the challenging task of prostate segmentation in CT imag…
MetricUNet: Synergistic Image- and Voxel-Level Learning for Precise CT Prostate Segmentation via Online Sampling
Kelei He, Chunfeng Lian, Ehsan Adeli +5
Fully convolutional networks (FCNs), including UNet and VNet, are widely-used network architectures for semantic segmentation in recent studies. However, conventional FCN is typica…
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…
Automatic Data Augmentation via Deep Reinforcement Learning for Effective Kidney Tumor Segmentation
Tiexin Qin, Ziyuan Wang, Kelei He +3
Conventional data augmentation realized by performing simple pre-processing operations (\eg, rotation, crop, \etc) has been validated for its advantage in enhancing the performance…