activity
20232025
most citedCMRxRecon: An open cardiac MRI dataset for the competition of accelerated image reconstruction

15 citations · 23 across the 7 of their papers we have counts for

collaborators

7 papers

eess.IV2025

Enabling Ultra-Fast Cardiovascular Imaging Across Heterogeneous Clinical Environments with A Generalist Foundation Model and Multimodal Database

Zi Wang, Mingkai Huang, Zhang Shi +61

Multimodal cardiovascular magnetic resonance (CMR) imaging provides comprehensive and non-invasive insights into cardiovascular disease (CVD) diagnosis and underlying mechanisms. D…

eess.IV2025★ 5 cited

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…

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

Sampling-Pattern-Agnostic MRI Reconstruction through Adaptive Consistency Enforcement with Diffusion Model

Anurag Malyala, Zhenlin Zhang, Chengyan Wang +1

Magnetic Resonance Imaging (MRI) is a powerful, non-invasive diagnostic tool; however, its clinical applicability is constrained by prolonged acquisition times. Whilst present deep…

eess.IV2024★ 1 cited

CMRxRecon2024: A Multi-Modality, Multi-View K-Space Dataset Boosting Universal Machine Learning for Accelerated Cardiac MRI

Zi Wang, Fanwen Wang, Chen Qin +29

Cardiac magnetic resonance imaging (MRI) has emerged as a clinically gold-standard technique for diagnosing cardiac diseases, thanks to its ability to provide diverse information w…

eess.IV2024★ 2 cited

The state-of-the-art in Cardiac MRI Reconstruction: Results of the CMRxRecon Challenge in MICCAI 2023

Jun Lyu, Chen Qin, Shuo Wang +47

Cardiac MRI, crucial for evaluating heart structure and function, faces limitations like slow imaging and motion artifacts. Undersampling reconstruction, especially data-driven alg…

cs.CV2023★ 15 cited

CMRxRecon: An open cardiac MRI dataset for the competition of accelerated image reconstruction

Chengyan Wang, Jun Lyu, Shuo Wang +25

Cardiac magnetic resonance imaging (CMR) has emerged as a valuable diagnostic tool for cardiac diseases. However, a limitation of CMR is its slow imaging speed, which causes patien…