3 papers
eess.IV2026
Potential and challenges of generative adversarial networks for super-resolution in 4D Flow MRI
Oliver Welin Odeback, Arivazhagan Geetha Balasubramanian, Jonas Schollenberger +9
4D Flow Magnetic Resonance Imaging (4D Flow MRI) enables non-invasive quantification of blood flow and hemodynamic parameters. However, its clinical application is limited by low s…
cs.CV2025
A Computational Pipeline for Advanced Analysis of 4D Flow MRI in the Left Atrium
Xabier Morales, Ayah Elsayed, Debbie Zhao +13
The left atrium (LA) plays a pivotal role in modulating left ventricular filling, but our comprehension of its hemodynamics is significantly limited by the constraints of conventio…
cs.LG2025
Deep learning for temporal super-resolution 4D Flow MRI
Pia Callmer, Mia Bonini, Edward Ferdian +5
4D Flow Magnetic Resonance Imaging (4D Flow MRI) is a non-invasive technique for volumetric, time-resolved blood flow quantification. However, apparent trade-offs between acquisiti…