7 citations · 10 across the 17 of their papers we have counts for
5 papers · 1 filter
Auxiliary Input in Training: Incorporating Catheter Features into Deep Learning Models for ECG-Free Dynamic Coronary Roadmapping
Yikang Liu, Lin Zhao, Eric Z. Chen +3
Dynamic coronary roadmapping is a technology that overlays the vessel maps (the "roadmap") extracted from an offline image sequence of X-ray angiography onto a live stream of X-ray…
Retrieval-augmented Few-shot Medical Image Segmentation with Foundation Models
Lin Zhao, Xiao Chen, Eric Z. Chen +3
Medical image segmentation is crucial for clinical decision-making, but the scarcity of annotated data presents significant challenges. Few-shot segmentation (FSS) methods show pro…
Federated Data Model
Xiao Chen, Shunan Zhang, Eric Z. Chen +4
In artificial intelligence (AI), especially deep learning, data diversity and volume play a pivotal role in model development. However, training a robust deep learning model often…
Spatiotemporal Diffusion Model with Paired Sampling for Accelerated Cardiac Cine MRI
Shihan Qiu, Shaoyan Pan, Yikang Liu +7
Current deep learning reconstruction for accelerated cardiac cine MRI suffers from spatial and temporal blurring. We aim to improve image sharpness and motion delineation for cine…
Clinically Feasible Diffusion Reconstruction for Highly-Accelerated Cardiac Cine MRI
Shihan Qiu, Shaoyan Pan, Yikang Liu +7
The currently limited quality of accelerated cardiac cine reconstruction may potentially be improved by the emerging diffusion models, but the clinically unacceptable long processi…