MRXCAT2.0: Synthesis of realistic numerical phantoms by combining left-ventricular shape learning, biophysical simulations and tissue texture generation.

Stefano BuosoThomas JoyceNico SchulthessSebastian Kozerke

Published in: Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance (2023)

MRXCAT2.0 offers synthesis of realistic images embedding population-based anatomical and functional variability and associated ground truth parameters to facilitate a standardized assessment of CMR acquisition, reconstruction and processing methods.

Keyphrases

left ventricular
deep learning
heart failure
molecular dynamics
convolutional neural network
optical coherence tomography
hypertrophic cardiomyopathy
acute myocardial infarction
machine learning
cardiac resynchronization therapy
atrial fibrillation
ejection fraction
monte carlo