89 citations · 256 across the 17 of their papers we have counts for
17 papers
Learning Spatially Decoupled Color Representations for Facial Image Colorization
Hangyan Zhu, Ming Liu, Chao Zhou +3
Image colorization methods have shown prominent performance on natural images. However, since humans are more sensitive to faces, existing methods are insufficient to meet the dema…
Efficient automatic segmentation for multi-level pulmonary arteries: The PARSE challenge
Gongning Luo, Kuanquan Wang, Jun Liu +27
Efficient automatic segmentation of multi-level (i.e. main and branch) pulmonary arteries (PA) in CTPA images plays a significant role in clinical applications. However, most exist…
The state-of-the-art 3D anisotropic intracranial hemorrhage segmentation on non-contrast head CT: The INSTANCE challenge
Xiangyu Li, Gongning Luo, Kuanquan Wang +31
Automatic intracranial hemorrhage segmentation in 3D non-contrast head CT (NCCT) scans is significant in clinical practice. Existing hemorrhage segmentation methods usually ignores…
Position-prior Clustering-based Self-attention Module for Knee Cartilage Segmentation
Dong Liang, Jun Liu, Kuanquan Wang +3
The morphological changes in knee cartilage (especially femoral and tibial cartilages) are closely related to the progression of knee osteoarthritis, which is expressed by magnetic…
ULTRA: Uncertainty-aware Label Distribution Learning for Breast Tumor Cellularity Assessment
Xiangyu Li, Xinjie Liang, Gongning Luo +3
Neoadjuvant therapy (NAT) for breast cancer is a common treatment option in clinical practice. Tumor cellularity (TC), which represents the percentage of invasive tumors in the tum…
Transformer Network for Significant Stenosis Detection in CCTA of Coronary Arteries
Xinghua Ma, Gongning Luo, Wei Wang +1
Coronary artery disease (CAD) has posed a leading threat to the lives of cardiovascular disease patients worldwide for a long time. Therefore, automated diagnosis of CAD has indisp…
The SARAS Endoscopic Surgeon Action Detection (ESAD) dataset: Challenges and methods
Vivek Singh Bawa, Gurkirt Singh, Francis KapingA +16
For an autonomous robotic system, monitoring surgeon actions and assisting the main surgeon during a procedure can be very challenging. The challenges come from the peculiar struct…
Weakly Supervised Arrhythmia Detection Based on Deep Convolutional Neural Network
Yang Liu, Kuanquan Wang, Qince Li +3
Supervised deep learning has been widely used in the studies of automatic ECG classification, which largely benefits from sufficient annotation of large datasets. However, most of…
A Global Benchmark of Algorithms for Segmenting Late Gadolinium-Enhanced Cardiac Magnetic Resonance Imaging
Zhaohan Xiong, Qing Xia, Zhiqiang Hu +41
Segmentation of cardiac images, particularly late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) widely used for visualizing diseased cardiac structures, is a crucial fir…
Short-time detection of QRS complexes using dual channels 1 based on U-Net and bidirectional long short-term memory
Runnan He, Yang Liu, Kuanquan Wang +4
Cardiovascular disease is associated with high rates of morbidity and mortality, and can be reflected by 19 abnormal features of electrocardiogram (ECG). Detecting changes in the Q…
Multi-step Cascaded Networks for Brain Tumor Segmentation
Xiangyu Li, Gongning Luo, Kuanquan Wang
Automatic brain tumor segmentation method plays an extremely important role in the whole process of brain tumor diagnosis and treatment. In this paper, we propose a multi-step casc…
An Automatic Cardiac Segmentation Framework based on Multi-sequence MR Image
Yashu Liu, Wei Wang, Kuanquan Wang +2
LGE CMR is an efficient technology for detecting infarcted myocardium. An efficient and objective ventricle segmentation method in LGE can benefit the location of the infarcted myo…
Automatic Detection of ECG Abnormalities by using an Ensemble of Deep Residual Networks with Attention
Yang Liu, Runnan He, Kuanquan Wang +4
Heart disease is one of the most common diseases causing morbidity and mortality. Electrocardiogram (ECG) has been widely used for diagnosing heart diseases for its simplicity and…
Focus On What's Important: Self-Attention Model for Human Pose Estimation
Guanxiong Sun, Chengqin Ye, Kuanquan Wang
Human pose estimation is an essential yet challenging task in computer vision. One of the reasons for this difficulty is that there are many redundant regions in the images. In thi…
VoxelAtlasGAN: 3D Left Ventricle Segmentation on Echocardiography with Atlas Guided Generation and Voxel-to-voxel Discrimination
Suyu Dong, Gongning Luo, Kuanquan Wang +5
3D left ventricle (LV) segmentation on echocardiography is very important for diagnosis and treatment of cardiac disease. It is not only because of that echocardiography is a real-…
Multi-views Fusion CNN for Left Ventricular Volumes Estimation on Cardiac MR Images
Gongning Luo, Suyu Dong, Kuanquan Wang +3
Left ventricular (LV) volumes estimation is a critical procedure for cardiac disease diagnosis. The objective of this paper is to address direct LV volumes prediction task. Methods…
Detail-preserving and Content-aware Variational Multi-view Stereo Reconstruction
Zhaoxin Li, Kuanquan Wang, Wangmeng Zuo +2
Accurate recovery of 3D geometrical surfaces from calibrated 2D multi-view images is a fundamental yet active research area in computer vision. Despite the steady progress in multi…