activity
20232026
most citedCMRxRecon: An open cardiac MRI dataset for the competition of accelerated image reconstruction

15 citations · 18 across the 7 of their papers we have counts for

collaborators

7 papers

cs.IR2026

From Trajectories to Phenotypes: Disease Progression as Structural Priors for Multi-organ Imaging Representation Learning

Zian Wang, Lizhen Lan, Guangming Wang +9

Imaging-derived phenotypes (IDPs) summarize multi-organ physiology but provide only static snapshots of diseases that evolve over time. In contrast, longitudinal electronic health…

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

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

An Empirical Study on the Fairness of Foundation Models for Multi-Organ Image Segmentation

Qin Li, Yizhe Zhang, Yan Li +11

The segmentation foundation model, e.g., Segment Anything Model (SAM), has attracted increasing interest in the medical image community. Early pioneering studies primarily concentr…

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…