2 citations · 2 across the 4 of their papers we have counts for
5 papers · 1 filter
DCRA-Net: Attention-Enabled Reconstruction Model for Dynamic Fetal Cardiac MRI
Denis Prokopenko, David F. A. Lloyd, Amedeo Chiribiri +2
Dynamic fetal heart magnetic resonance imaging (MRI) presents unique challenges due to the fast heart rate of the fetus compared to adult subjects and uncontrolled fetal motion. Th…
Improved 3D Whole Heart Geometry from Sparse CMR Slices
Yiyang Xu, Hao Xu, Matthew Sinclair +6
Cardiac magnetic resonance (CMR) imaging and computed tomography (CT) are two common non-invasive imaging methods for assessing patients with cardiovascular disease. CMR typically…
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…
Deep learning-based prediction of kinetic parameters from myocardial perfusion MRI
Cian M. Scannell, Piet van den Bosch, Amedeo Chiribiri +3
The quantification of myocardial perfusion MRI has the potential to provide a fast, automated and user-independent assessment of myocardial ischaemia. However, due to the relativel…
Hierarchical Bayesian myocardial perfusion quantification
Cian M. Scannell, Amedeo Chiribiri, Adriana D. M. Villa +2
Purpose: Tracer-kinetic models can be used for the quantitative assessment of contrast-enhanced MRI data. However, the model-fitting can produce unreliable results due to the limit…