3 papers
eess.IV2026
GHOST-CAT: An Efficient and Practical Network for Mesh Generation from 3D Echocardiography
Edward Ferdian, Debbie Zhao, Alistair A. Young +1
Recent advances in deep learning have significantly accelerated cardiac imaging workflows, from segmentation to the generation of meshes for computational modelling. Nevertheless,…
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.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…