Fast Compressed Sensing of 3D Radial T(1) Mapping with Different Sparse and Low-Rank Models

Knowledge of the relative performance of the well-known sparse and low-rank compressed sensing models with 3D radial quantitative magnetic resonance imaging acquisitions is limited. We use 3D radial T(1) relaxation time mapping data to compare the total variation, low-rank, and Huber penalty functio...

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Detalles Bibliográficos
Autores principales: Paajanen, Antti, Hanhela, Matti, Hänninen, Nina, Nykänen, Olli, Kolehmainen, Ville, Nissi, Mikko J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10455972/
https://www.ncbi.nlm.nih.gov/pubmed/37623683
http://dx.doi.org/10.3390/jimaging9080151

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10455972/
https://www.ncbi.nlm.nih.gov/pubmed/37623683
http://dx.doi.org/10.3390/jimaging9080151

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