4D Flow MRI promises opportunities for non-invasive mapping of neurovascular hemodynamics, but its clinical utility faces trade-offs between resolution, acquisition time, and noise. Deep learning-based super-resolution offers a post-scan solution, but supervised approaches require paired or domain-specific data, while...
Oliver Welin Odeback, Nerea González-Aranceta, Sebastián Jofre et al.· 0 citations
Magnetic resonance imaging (MRI) can estimate three-dimensional (3D) time-resolved blood velocity fields using 4D-flow MRI, providing rich relative pressure field information. Clinical alternatives-catheterization and Doppler echocardiography-provide one-dimensional pressure drops. While the accuracy of one-dimensional...
Brandon Hardy, Judith Zimmermann, Vincent Lechner et al.· IEEE Transactions on Medical...· 0 citations
Valve dysfunction is a major threat to long-term success in left ventricle assist device (LVAD) therapy, with direct implications for right heart performance. In this study, we apply a patient-specific, image-based computational modeling framework to evaluate the hemodynamic impact of simulated mitral and aortic valve...
Mia Bonini, Michael Ferguson, Marc Hirshvogel et al.· arXiv.org· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.