86 citations · 133 across the 10 of their papers we have counts for
Showing 2020Show all
2 papers · 1 filter
eess.IV2020★ 86 cited
Physics-informed neural networks for myocardial perfusion MRI quantification
Rudolf L. M. van Herten, Amedeo Chiribiri, Marcel Breeuwer +2
Tracer-kinetic models allow for the quantification of kinetic parameters such as blood flow from dynamic contrast-enhanced magnetic resonance (MR) images. Fitting the observed data…
eess.IV2020
Domain-Adversarial Learning for Multi-Centre, Multi-Vendor, and Multi-Disease Cardiac MR Image Segmentation
Cian M. Scannell, Amedeo Chiribiri, Mitko Veta
Cine cardiac magnetic resonance (CMR) has become the gold standard for the non-invasive evaluation of cardiac function. In particular, it allows the accurate quantification of func…