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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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| Опубликовано в: : | Vis Comput Ind Biomed Art |
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| Главные авторы: | , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Springer Singapore
2020
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| Предметы: | |
| Online-ссылка: | 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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