Accelerating whole-heart 3D T2 mapping: Impact of undersampling strategies and reconstruction techniques.

Dan ZhuHaiyan DingM Muz ZvimanHenry HalperinMichael SchärDaniel A Herzka

Published in: PloS one (2021)

Retrospective exploration of undersampling and reconstruction in 3D whole-heart T2 parametric mapping revealed that maps were more sensitive to undersampling than images, presenting a more stringent limiting factor on Rnet. The combination of VDR sampling patterns with model-based or joint-sparsity SENSE reconstructions were more robust for Rnet>3.

Keyphrases

high resolution
heart failure
high density
atrial fibrillation
deep learning
convolutional neural network
single cell
optical coherence tomography
magnetic resonance imaging
machine learning
image quality