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eess.IV2025
Extreme Cardiac MRI Analysis under Respiratory Motion: Results of the CMRxMotion Challenge
Kang Wang, Chen Qin, Zhang Shi +46
Deep learning models have achieved state-of-the-art performance in automated Cardiac Magnetic Resonance (CMR) analysis. However, the efficacy of these models is highly dependent on…
eess.IV2022
Cardiac Segmentation using Transfer Learning under Respiratory Motion Artifacts
Carles Garcia-Cabrera, Eric Arazo, Kathleen M. Curran +2
Methods that are resilient to artifacts in the cardiac magnetic resonance imaging (MRI) while performing ventricle segmentation, are crucial for ensuring quality in structural and…