Deep-learning based super-resolution for 3D isotropic coronary MR angiography in less than a minute.
3D whole-heart
coronary MR angiography
deep learning
super resolution
Journal
Magnetic resonance in medicine
ISSN: 1522-2594
Titre abrégé: Magn Reson Med
Pays: United States
ID NLM: 8505245
Informations de publication
Date de publication:
11 2021
11 2021
Historique:
revised:
08
06
2021
received:
18
01
2021
accepted:
11
06
2021
pubmed:
10
7
2021
medline:
27
10
2021
entrez:
9
7
2021
Statut:
ppublish
Résumé
To develop and evaluate a novel and generalizable super-resolution (SR) deep-learning framework for motion-compensated isotropic 3D coronary MR angiography (CMRA), which allows free-breathing acquisitions in less than a minute. Undersampled motion-corrected reconstructions have enabled free-breathing isotropic 3D CMRA in ~5-10 min acquisition times. In this work, we propose a deep-learning-based SR framework, combined with non-rigid respiratory motion compensation, to shorten the acquisition time to less than 1 min. A generative adversarial network (GAN) is proposed consisting of two cascaded Enhanced Deep Residual Network generator, a trainable discriminator, and a perceptual loss network. A 16-fold increase in spatial resolution is achieved by reconstructing a high-resolution (HR) isotropic CMRA (0.9 mm SR-CMRA showed statistically significant (P < .001) improved vessel sharpness 34.1% ± 12.3% and length 41.5% ± 8.1% compared with LR-CMRA. Good generalization to input resolution and image/patch-level processing was found. SR-CMRA enabled recovery of coronary stenosis similar to HR-CMRA with comparable qualitative performance. The proposed SR-CMRA provides a 16-fold increase in spatial resolution with comparable image quality to HR-CMRA while reducing the predictable scan time to <1 min.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
2837-2852Subventions
Organisme : British Heart Foundation
ID : PG/18/59/33955
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/L009676/1
Pays : United Kingdom
Organisme : Wellcome Trust
ID : NS/A000049/1
Pays : United Kingdom
Organisme : British Heart Foundation
ID : FS/CRTF/20/24011
Pays : United Kingdom
Organisme : British Heart Foundation
ID : RG/20/1/34802
Pays : United Kingdom
Organisme : Department of Health
Pays : United Kingdom
Organisme : British Heart Foundation
ID : RE/18/2/34213
Pays : United Kingdom
Informations de copyright
© 2021 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.
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