Optimal compressed sensing reconstructions of fMRI using 2D deterministic and stochastic sampling geometries

BACKGROUND: Compressive sensing can provide a promising framework for accelerating fMRI image acquisition by allowing reconstructions from a limited number of frequency-domain samples. Unfortunately, the majority of compressive sensing studies are based on stochastic sampling geometries that cannot...

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Detalles Bibliográficos
Autores principales: Jeromin, Oliver, Pattichis, Marios S, Calhoun, Vince D
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3807755/
https://www.ncbi.nlm.nih.gov/pubmed/22607467
http://dx.doi.org/10.1186/1475-925X-11-25

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3807755/
https://www.ncbi.nlm.nih.gov/pubmed/22607467
http://dx.doi.org/10.1186/1475-925X-11-25

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