Motion artifact removal in coronary CT angiography based on generative adversarial networks.

Lu ZhangBeibei JiangQiang ChenLingyun WangKeke ZhaoYaping ZhangRozemarijn VliegenthartXueqian Xie

Published in: European radiology (2022)

• A generative adversarial network greatly reduced motion artifacts in coronary CT angiography and improved image quality. • GAN-generated images improved diagnosis accuracy of identifying no, < 50%, and ≥ 50% stenosis.

Keyphrases

image quality
coronary artery disease
coronary artery
computed tomography
dual energy
high speed
deep learning
aortic stenosis
convolutional neural network
optical coherence tomography
transcatheter aortic valve replacement
magnetic resonance
mass spectrometry
aortic valve