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Non-iterative image reconstruction from sparse magnetic resonance imaging radial data without priors
The state-of-the-art approaches for image reconstruction using under-sampled k-space data are compressed sensing based. They are iterative algorithms that optimize objective functions with spatial and/or temporal constraints. This paper proposes a non-iterative algorithm to estimate the un-measured...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer Singapore
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7176778/ https://www.ncbi.nlm.nih.gov/pubmed/32323097 http://dx.doi.org/10.1186/s42492-020-00044-y |