6 citations · 10 across the 9 of their papers we have counts for
9 papers
AI-Enabled Accurate Non-Invasive Assessment of Pulmonary Hypertension Progression via Multi-Modal Echocardiography
Jiewen Yang, Taoran Huang, Shangwei Ding +9
Echocardiographers can detect pulmonary hypertension using Doppler echocardiography; however, accurately assessing its progression often proves challenging. Right heart catheteriza…
DeepSparse: A Foundation Model for Sparse-View CBCT Reconstruction
Yiqun Lin, Jixiang Chen, Hualiang Wang +4
Cone-beam computed tomography (CBCT) is a critical 3D imaging technology in the medical field, while the high radiation exposure required for high-quality imaging raises significan…
CardiacNet: Learning to Reconstruct Abnormalities for Cardiac Disease Assessment from Echocardiogram Videos
Jiewen Yang, Yiqun Lin, Bin Pu +3
Echocardiogram video plays a crucial role in analysing cardiac function and diagnosing cardiac diseases. Current deep neural network methods primarily aim to enhance diagnosis accu…
Bidirectional Recurrence for Cardiac Motion Tracking with Gaussian Process Latent Coding
Jiewen Yang, Yiqun Lin, Bin Pu +1
Quantitative analysis of cardiac motion is crucial for assessing cardiac function. This analysis typically uses imaging modalities such as MRI and Echocardiograms that capture deta…
C^2RV: Cross-Regional and Cross-View Learning for Sparse-View CBCT Reconstruction
Yiqun Lin, Jiewen Yang, Hualiang Wang +3
Cone beam computed tomography (CBCT) is an important imaging technology widely used in medical scenarios, such as diagnosis and preoperative planning. Using fewer projection views…
DiffCMR: Fast Cardiac MRI Reconstruction with Diffusion Probabilistic Models
Tianqi Xiang, Wenjun Yue, Yiqun Lin +3
Performing magnetic resonance imaging (MRI) reconstruction from under-sampled k-space data can accelerate the procedure to acquire MRI scans and reduce patients' discomfort. The re…
GraphEcho: Graph-Driven Unsupervised Domain Adaptation for Echocardiogram Video Segmentation
Jiewen Yang, Xinpeng Ding, Ziyang Zheng +2
Echocardiogram video segmentation plays an important role in cardiac disease diagnosis. This paper studies the unsupervised domain adaption (UDA) for echocardiogram video segmentat…
GL-Fusion: Global-Local Fusion Network for Multi-view Echocardiogram Video Segmentation
Ziyang Zheng, Jiewen Yang, Xinpeng Ding +2
Cardiac structure segmentation from echocardiogram videos plays a crucial role in diagnosing heart disease. The combination of multi-view echocardiogram data is essential to enhanc…
Towards High-Quality Temporal Action Detection with Sparse Proposals
Jiannan Wu, Peize Sun, Shoufa Chen +4
Temporal Action Detection (TAD) is an essential and challenging topic in video understanding, aiming to localize the temporal segments containing human action instances and predict…