78 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Fudan UniversityCN14 papers
- Fudan University Shanghai Cancer CenterCN5 papers
- Imperial College LondonGB4 papers
- The University of SydneyAU3 papers
- Chinese University of Hong KongHK2 papers
- Eindhoven University of TechnologyNL2 papers
- Hong Kong University of Science and TechnologyHK2 papers
- MRC London Institute of Medical SciencesGB2 papers
- Shanghai Institute of Computing TechnologyCN2 papers
- Shanghai Jiao Tong UniversityCN2 papers
- Shanghai Public Health Clinical CenterCN2 papers
- ShanghaiTech UniversityCN2 papers
23 papers
Extreme Cardiac MRI Analysis under Respiratory Motion: Results of the CMRxMotion Challenge
Kang Wang, Chen Qin, Zhang Shi +46
Deep learning models have achieved state-of-the-art performance in automated Cardiac Magnetic Resonance (CMR) analysis. However, the efficacy of these models is highly dependent on…
A personalized time-resolved 3D mesh generative model for unveiling normal heart dynamics
Mengyun Qiao, Kathryn A McGurk, Shuo Wang +3
Understanding the structure and motion of the heart is crucial for diagnosing and managing cardiovascular diseases, the leading cause of global death. There is wide variation in ca…
Test-time generative augmentation for medical image segmentation
Xiao Ma, Yuhui Tao, Zetian Zhang +7
Medical image segmentation is critical for clinical diagnosis, treatment planning, and monitoring, yet segmentation models often struggle with uncertainties stemming from occlusion…
CLIP in Medical Imaging: A Survey
Zihao Zhao, Yuxiao Liu, Han Wu +8
Contrastive Language-Image Pre-training (CLIP), a simple yet effective pre-training paradigm, successfully introduces text supervision to vision models. It has shown promising resu…
AdaMSS: Adaptive Multi-Modality Segmentation-to-Survival Learning for Survival Outcome Prediction from PET/CT Images
Mingyuan Meng, Bingxin Gu, Michael Fulham +4
Survival prediction is a major concern for cancer management. Deep survival models based on deep learning have been widely adopted to perform end-to-end survival prediction from me…
Multi-organ segmentation: a progressive exploration of learning paradigms under scarce annotation
Shiman Li, Haoran Wang, Yucong Meng +2
Precise delineation of multiple organs or abnormal regions in the human body from medical images plays an essential role in computer-aided diagnosis, surgical simulation, image-gui…
CHeart: A Conditional Spatio-Temporal Generative Model for Cardiac Anatomy
Mengyun Qiao, Shuo Wang, Huaqi Qiu +4
Two key questions in cardiac image analysis are to assess the anatomy and motion of the heart from images; and to understand how they are associated with non-imaging clinical facto…
Robust Point Cloud Registration Framework Based on Deep Graph Matching(TPAMI Version)
Kexue Fu, Jiazheng Luo, Xiaoyuan Luo +3
3D point cloud registration is a fundamental problem in computer vision and robotics. Recently, learning-based point cloud registration methods have made great progress. However, t…
MyoPS-Net: Myocardial Pathology Segmentation with Flexible Combination of Multi-Sequence CMR Images
Junyi Qiu, Lei Li, Sihan Wang +4
Myocardial pathology segmentation (MyoPS) can be a prerequisite for the accurate diagnosis and treatment planning of myocardial infarction. However, achieving this segmentation is…
Towards Label-efficient Automatic Diagnosis and Analysis: A Comprehensive Survey of Advanced Deep Learning-based Weakly-supervised, Semi-supervised and Self-supervised Techniques in Histopathological Image Analysis
Linhao Qu, Siyu Liu, Xiaoyu Liu +2
Histopathological images contain abundant phenotypic information and pathological patterns, which are the gold standards for disease diagnosis and essential for the prediction of p…
A clinically relevant online patient QA solution with daily CT scans and EPID-based in vivo dosimetry: A feasible study on rectal cancer
Liyuan Chen, Zhiyuan Zhang, Lei Yu +8
Adaptive radiation therapy (ART) could protect organs at risk (OARs) while maintain high dose coverage to targets. However, there still lack efficient online patient QA methods. We…
DeepMTS: Deep Multi-task Learning for Survival Prediction in Patients with Advanced Nasopharyngeal Carcinoma using Pretreatment PET/CT
Mingyuan Meng, Bingxin Gu, Lei Bi +3
Nasopharyngeal Carcinoma (NPC) is a malignant epithelial cancer arising from the nasopharynx. Survival prediction is a major concern for NPC patients, as it provides early prognost…
Non-invasive Assessment of Hepatic Venous Pressure Gradient (HVPG) Based on MR Flow Imaging and Computational Fluid Dynamics
Kexin Wang, Shuo Wang, Minghua Xiong +2
Clinically significant portal hypertension (CSPH) is a severe complication of chronic liver disease associated with cirrhosis, which is diagnosed by the measurement of hepatic veno…
Prediction of 5-year Progression-Free Survival in Advanced Nasopharyngeal Carcinoma with Pretreatment PET/CT using Multi-Modality Deep Learning-based Radiomics
Bingxin Gu, Mingyuan Meng, Lei Bi +3
Objective: Deep Learning-based Radiomics (DLR) has achieved great success in medical image analysis and has been considered a replacement for conventional radiomics that relies on…
Equilibrium and transient thermodynamics: A unified dissipaton-space approach
Hong Gong, Yao Wang, Hou-Dao Zhang +4
This work presents a unified dissipaton-equation-of-motion (DEOM) theory and its evaluations on the Helmholtz free energy change due to the isotherm mixing of two isolated subsyste…
Data-driven dose calculation algorithm based on deep learning
Jiawei Fan, Lei Xing, Peng Dong +3
In this study we performed a feasibility investigation on implementing a fast and accurate dose calculation based on a deep learning technique. A two dimensional (2D) fluence map w…
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…
A Novel Method for the Absolute Pose Problem with Pairwise Constraints
Yinlong Liu, Xuechen Li, Manning Wang +3
Absolute pose estimation is a fundamental problem in computer vision, and it is a typical parameter estimation problem, meaning that efforts to solve it will always suffer from out…
Organ at Risk Segmentation in Head and Neck CT Images by Using a Two-Stage Segmentation Framework Based on 3D U-Net
Yueyue Wang, Liang Zhao, Zhijian Song +1
Accurate segmentation of organ at risk (OAR) play a critical role in the treatment planning of image guided radiation treatment of head and neck cancer. This segmentation task is c…
Denoising of 3D magnetic resonance images with multi-channel residual learning of convolutional neural network
Dongsheng Jiang, Weiqiang Dou, Luc Vosters +3
The denoising of magnetic resonance (MR) images is a task of great importance for improving the acquired image quality. Many methods have been proposed in the literature to retriev…
On the role of T cells in determining recovery time from influenza virus infection
Pengxing Cao, Zhongfang Wang, Ada W. C. Yan +5
Myriad experiments have identified an important role for T cell response mechanisms in determining recovery from influenza A virus infection. Animal models of influenza…
Spatio-temporal Granger causality: a new framework
Qiang Luo, Wenlian Lu, Wei Cheng +4
That physiological oscillations of various frequencies are present in fMRI signals is the rule, not the exception. Herein, we propose a novel theoretical framework, spatio-temporal…
Capillary Rise in Tubes with Sharp Grooves
Lei-Han Tang, Yu Tang
Liquid in grooved capillaries, made by e.g. inserting a plate in a cylindrical tube, exhibits unusual spreading and flow properties. One example is capillary rise, where a long, up…