HDNLS: Hybrid Deep-Learning and Non-Linear Least Squares-Based Method for Fast Multi-Component T1ρ M...
HDNLS: Hybrid Deep-Learning and Non-Linear Least Squares-Based Method for Fast Multi-Component T1ρ Mapping in the Knee Joint
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Switzerland: MDPI AG
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English
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Switzerland: MDPI AG
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Non-linear least squares (NLS) methods are commonly used for quantitative magnetic resonance imaging (MRI), especially for multi-exponential T1ρ mapping, which provides precise parameter estimation for different relaxation models in tissues, such as mono-exponential (ME), bi-exponential (BE), and stretched-exponential (SE) models. However, NLS may...
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Full title
HDNLS: Hybrid Deep-Learning and Non-Linear Least Squares-Based Method for Fast Multi-Component T1ρ Mapping in the Knee Joint
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TN_cdi_doaj_primary_oai_doaj_org_article_be7646c68da740899f7bf2bf016afd9d
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_be7646c68da740899f7bf2bf016afd9d
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ISSN
2306-5354
E-ISSN
2306-5354
DOI
10.3390/bioengineering12010008
