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cs.CV2026
Foundation Models Adaptation for Multi-View Multi-modal Cardiac MRI Segmentation and Direct Ejection Fraction Estimation
Sina Amirrajab, Cian M Scannell, Volker Vehof +2
Foundation models have shown strong transferability in cardiac MRI (CMR), but their effectiveness for heterogeneous multi-view and multi-sequence CMR analysis remains unclear. In t…
cs.CV2025
Deep learning motion correction of quantitative stress perfusion cardiovascular magnetic resonance
Noortje I. P. Schueler, Nathan C. K. Wong, Richard J. Crawley +3
Background: Quantitative stress perfusion cardiovascular magnetic resonance (CMR) is a powerful tool for assessing myocardial ischemia. Motion correction is essential for accurate…
cs.CV2024
Self-supervised Pretraining for Cardiovascular Magnetic Resonance Cine Segmentation
Rob A. J. de Mooij, Josien P. W. Pluim, Cian M. Scannell
Self-supervised pretraining (SSP) has shown promising results in learning from large unlabeled datasets and, thus, could be useful for automated cardiovascular magnetic resonance (…