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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...

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Detalhes bibliográficos
Publicado no:Vis Comput Ind Biomed Art
Main Authors: Zeng, Gengsheng L., DiBella, Edward V.
Formato: Artigo
Idioma:Inglês
Publicado em: Springer Singapore 2020
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7176778/
https://ncbi.nlm.nih.gov/pubmed/32323097
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s42492-020-00044-y
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