Joint MAPLE: Accelerated joint T
parameter mapping
quantitative MRI
scan-specific deep learning
self-supervised networks
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:
05 Jan 2024
05 Jan 2024
Historique:
revised:
30
10
2023
received:
19
07
2023
accepted:
11
12
2023
medline:
5
1
2024
pubmed:
5
1
2024
entrez:
5
1
2024
Statut:
aheadofprint
Résumé
Quantitative MRI finds important applications in clinical and research studies. However, it is encoding intensive and may suffer from prohibitively long scan times. Accelerated MR parameter mapping techniques have been developed to help address these challenges. Here, an accelerated joint T Proposed framework, Joint MAPLE, includes parallel imaging, signal modeling, and data consistency blocks which are optimized jointly in a combined loss function. A scan-specific self-supervised reconstruction is embedded into the framework, which takes advantage of multi-contrast data from a multi-echo, multi-flip angle, gradient echo acquisition. In comparison with parallel reconstruction techniques powered by low-rank methods, emerging scan specific networks, and model-based Joint MAPLE enables higher fidelity parameter estimation at high acceleration rates by synergistically combining parallel imaging and model-based parameter mapping and exploiting multi-echo, multi-flip angle datasets. Utilizing a scan-specific self-supervised reconstruction obviates the need for large data sets for training while improving the parameter estimation ability.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : NIH HHS
ID : P41 EB030006
Pays : United States
Organisme : NIH HHS
ID : R01 EB028797
Pays : United States
Organisme : NIH HHS
ID : R01 EB032378
Pays : United States
Organisme : NIH HHS
ID : R03 EB031175
Pays : United States
Organisme : NIH HHS
ID : U01 EB025162
Pays : United States
Organisme : NIH HHS
ID : U01 EB026996
Pays : United States
Organisme : NIH HHS
ID : UG3EB034875
Pays : United States
Informations de copyright
© 2024 International Society for Magnetic Resonance in Medicine.
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