Artifact reduction in free-breathing, free-running myocardial perfusion imaging with interleaved non-selective RF excitations.

Hassan Haji-Valizadeh Rui Guo Selcuk KucukseymenXiaoying CaiJennifer RodriguezPatrick PierceBeth GodduWarren ManningReza Nezafat

Published in: Magnetic resonance in medicine (2021)

Non-selective RF excitations interleaved between slice-selective excitations can reduce image artifacts in free-breathing, ungated perfusion images. Further studies are warranted to assess the diagnostic accuracy of the proposed solution for evaluating myocardial ischemia.

Keyphrases

deep learning
image quality
high resolution
left ventricular
high intensity
magnetic resonance imaging
convolutional neural network
optical coherence tomography
machine learning
magnetic resonance
atrial fibrillation
contrast enhanced
fluorescence imaging