2 citations · 2 across the 1 of their papers we have counts for
3 papers
eess.IV2025
Towards Modality- and Sampling-Universal Learning Strategies for Accelerating Cardiovascular Imaging: Summary of the CMRxRecon2024 Challenge
Fanwen Wang, Zi Wang, Yan Li +60
Cardiovascular health is vital to human well-being, and cardiac magnetic resonance (CMR) imaging is considered the {clinical reference standard} for diagnosing cardiovascular disea…
eess.IV2024★ 2 cited
DARCS: Memory-Efficient Deep Compressed Sensing Reconstruction for Acceleration of 3D Whole-Heart Coronary MR Angiography
Zhihao Xue, Fan Yang, Juan Gao +5
Three-dimensional coronary magnetic resonance angiography (CMRA) demands reconstruction algorithms that can significantly suppress the artifacts from a heavily undersampled acquisi…
eess.IV2023
Improve Myocardial Strain Estimation based on Deformable Groupwise Registration with a Locally Low-Rank Dissimilarity Metric
Haiyang Chen, Juan Gao, Zhuo Chen +5
Background: Current mainstream cardiovascular magnetic resonance-feature tracking (CMR-FT) methods, including optical flow and pairwise registration, often suffer from the drift ef…