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Found 4 papers, 1 papers with code
Opportunities for machine learning in scientific discovery
Technological advancements have substantially increased computational power and data availability, enabling the application of powerful machine-learning (ML) techniques across various fields.
Generalized super-resolution 4D Flow MRI $\unicode{x2013}$ using ensemble learning to extend across the cardiovascular system
4D Flow Magnetic Resonance Imaging (4D Flow MRI) is a non-invasive measurement technique capable of quantifying blood flow across the cardiovascular system.
Morphology-based non-rigid registration of coronary computed tomography and intravascular images through virtual catheter path optimization
We formulate the problem in terms of finding the optimal \emph{virtual catheter path} that samples the CCTA data to recapitulate the coronary artery morphology found in the intravascular image.
Non-invasive hemodynamic analysis for aortic regurgitation using computational fluid dynamics and deep learning
Changes in cardiovascular hemodynamics are closely related to the development of aortic regurgitation, a type of valvular heart disease.
