4 papers
HierAdaptMR: Cross-Center Cardiac MRI Reconstruction with Hierarchical Feature Adapters
Ruru Xu, Ilkay Oksuz
Deep learning-based cardiac MRI reconstruction faces significant domain shift challenges when deployed across multiple clinical centers with heterogeneous scanner configurations an…
Adaptive k-space Radial Sampling for Cardiac MRI with Reinforcement Learning
Ruru Xu, Ilkay Oksuz
Accelerated Magnetic Resonance Imaging (MRI) requires careful optimization of k-space sampling patterns to balance acquisition speed and image quality. While recent advances in dee…
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…
HyperCMR: Enhanced Multi-Contrast CMR Reconstruction with Eagle Loss
Ruru Xu, Caner Özer, Ilkay Oksuz
Accelerating image acquisition for cardiac magnetic resonance imaging (CMRI) is a critical task. CMRxRecon2024 challenge aims to set the state of the art for multi-contrast CMR rec…