Deep Learning Synthesis of White-Blood From Dark-Blood Late Gadolinium Enhancement Cardiac Magnetic Resonance.

Tim J M JaspersBibi MartensRichard CrawleyLamis JadaSina AmirrajabMarcel BreeuwerRobert J HoltackersAmedeo ChiribiriCian M Scannell

Published in: Investigative radiology (2024)

This study proposed a CycleGAN model to generate synthetic WB-LGE from DB-LGE images to allow assessment of both image contrasts without additional scan time. This work represents a clinically focused assessment of synthetic medical images generated by artificial intelligence, a topic with significant potential for a multitude of applications. However, further evaluation is warranted before clinical adoption.

Keyphrases

deep learning
artificial intelligence
convolutional neural network
magnetic resonance
big data
machine learning
computed tomography
healthcare
contrast enhanced
left ventricular
heart failure
risk assessment