From the 1 of 5 linked papers with an AI index.
5 papers
Motion-Conditioned Multi-View Fusion for Myocardial Infarction Localization from Echocardiography
Guang Yang, Wentian Xu, Siyu Wang +3
The paper introduces MCF-Net, a motion-guided multi-view fusion framework that combines sparse motion cues with a pretrained Echo foundation model to locate myocardial infarction s…
Learning from Acquisition: Metadata-driven Multimodal Pre-training for Cardiac MRI
Xueyi Fu, Liwei Hu, Zi Wang +1
Cardiac magnetic resonance imaging (CMR) routinely records structured acquisition metadata, yet most CMR foundation models rely primarily on image-only pre-training and leave this…
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…
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…
Contrast-Free Myocardial Scar Segmentation in Cine MRI using Motion and Texture Fusion
Guang Yang, Jingkun Chen, Xicheng Sheng +5
Late gadolinium enhancement MRI (LGE MRI) is the gold standard for the detection of myocardial scars for post myocardial infarction (MI). LGE MRI requires the injection of a contra…