8 papers
Adapting Frozen Mono-modal Backbones for Multi-modal Registration via Contrast-Agnostic Instance Optimization
Yi Zhang, Yidong Zhao, Qian Tao
Deformable image registration remains a central challenge in medical image analysis, particularly under multi-modal scenarios where intensity distributions vary significantly acros…
Learn2Reg 2024: New Benchmark Datasets Driving Progress on New Challenges
Lasse Hansen, Wiebke Heyer, Christoph Großbröhmer +51
Medical image registration is critical for clinical applications, and fair benchmarking of different methods is essential for monitoring ongoing progress in the field. To date, the…
Reverse Imaging for Wide-spectrum Generalization of Cardiac MRI Segmentation
Yidong Zhao, Peter Kellman, Hui Xue +5
Pretrained segmentation models for cardiac magnetic resonance imaging (MRI) struggle to generalize across different imaging sequences due to significant variations in image contras…
Bridging Classical and Learning-based Iterative Registration through Deep Equilibrium Models
Yi Zhang, Yidong Zhao, Qian Tao
Deformable medical image registration is traditionally formulated as an optimization problem. While classical methods solve this problem iteratively, recent learning-based approach…
Physics-Informed Neural ODEs for Temporal Dynamics Modeling in Cardiac T1 Mapping
Nuno Capitão, Yi Zhang, Yidong Zhao +1
Spin-lattice relaxation time () is an important biomarker in cardiac parametric mapping for characterizing myocardial tissue and diagnosing cardiomyopathies. Conventional Modi…
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…