5 citations · 8 across the 8 of their papers we have counts for
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Automated Labeling of Intracranial Arteries with Uncertainty Quantification Using Deep Learning
Javier Bisbal, Patrick Winter, Sebastian Jofre +10
Accurate anatomical labeling of intracranial arteries is essential for cerebrovascular diagnosis and hemodynamic analysis but remains time-consuming and subject to interoperator va…
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…
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…
Comprehensive Analysis of Relative Pressure Estimation in Type B Aortic Dissection Utilizing 4D-Flow MRI
Brandon Hardy, Judith Zimmermann, Vincent Lechner +6
Magnetic resonance imaging (MRI) can estimate three-dimensional (3D) time-resolved blood velocity fields using 4D-flow MRI, providing rich relative pressure field information. Clin…
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…