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Found 5 papers, 3 papers with code
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.
WSSNet: Aortic Wall Shear Stress Estimation Using Deep Learning on 4D Flow MRI
The algorithm was trained on 37 patient-specific geometries and velocity sheets.
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.
4DFlowNet: Super-Resolution 4D Flow MRI using Deep Learning and Computational Fluid Dynamics
4D-flow magnetic resonance imaging (MRI) is an emerging imaging technique where spatiotemporal 3D blood velocity can be captured with full volumetric coverage in a single non-invasive examination.
Fully Automated Myocardial Strain Estimation from CMR Tagged Images using a Deep Learning Framework in the UK Biobank
The fully automatic framework consisted of 1) a convolutional neural network (CNN) for localization, and 2) a combination of a recurrent neural network (RNN) and a CNN to detect and track the myocardial landmarks through the image sequence for each slice.
