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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...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2012
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| 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 |