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Reconstruction of Undersampled Big Dynamic MRI Data Using Non-Convex Low-Rank and Sparsity Constraints
Dynamic magnetic resonance imaging (MRI) has been extensively utilized for enhancing medical living environment visualization, however, in clinical practice it often suffers from long data acquisition times. Dynamic imaging essentially reconstructs the visual image from raw (k,t)-space measurements,...
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| Vydáno v: | Sensors (Basel) |
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| Hlavní autoři: | , , , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
MDPI
2017
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5375795/ https://ncbi.nlm.nih.gov/pubmed/28273827 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s17030509 |
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