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Low-Rank and Sparse Decomposition Model for Accelerating Dynamic MRI Reconstruction
The reconstruction of dynamic magnetic resonance imaging (dMRI) from partially sampled k-space data has to deal with a trade-off between the spatial resolution and temporal resolution. In this paper, a low-rank and sparse decomposition model is introduced to resolve this issue, which is formulated a...
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| Опубликовано в: : | J Healthc Eng |
|---|---|
| Главные авторы: | , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Hindawi
2017
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5591906/ https://ncbi.nlm.nih.gov/pubmed/29093806 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2017/9856058 |
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