10 citations · 10 across the 2 of their papers we have counts for
4 papers · 1 filter
Physics-informed self-supervised deep learning reconstruction for accelerated first-pass perfusion cardiac MRI
Elena Martín-González, Ebraham Alskaf, Amedeo Chiribiri +4
First-pass perfusion cardiac magnetic resonance (FPP-CMR) is becoming an essential non-invasive imaging method for detecting deficits of myocardial blood flow, allowing the assessm…
Deep Learning methods for automatic evaluation of delayed enhancement-MRI. The results of the EMIDEC challenge
Alain Lalande, Zhihao Chen, Thibaut Pommier +30
A key factor for assessing the state of the heart after myocardial infarction (MI) is to measure whether the myocardium segment is viable after reperfusion or revascularization the…
Automatic Myocardial Disease Prediction From Delayed-Enhancement Cardiac MRI and Clinical Information
Ana Lourenço, Eric Kerfoot, Irina Grigorescu +3
Delayed-enhancement cardiac magnetic resonance (DE-CMR)provides important diagnostic and prognostic information on myocardial viability. The presence and extent of late gadolinium…
Left atrial ejection fraction estimation using SEGANet for fully automated segmentation of CINE MRI
Ana Lourenço, Eric Kerfoot, Connor Dibblin +7
Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, characterised by a rapid and irregular electrical activation of the atria. Treatments for AF are often ine…