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Recovering task fMRI signals from highly under-sampled data with low-rank and temporal subspace constraints
Recent developments in highly accelerated fMRI data acquisition have employed low-rank and/or sparsity constraints for image reconstruction, as an alternative to conventional, time-independent parallel imaging. When under-sampling factors are high or the signals of interest are low-variance, however...
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| Pubblicato in: | Neuroimage |
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| Autori principali: | , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Academic Press
2018
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5953310/ https://ncbi.nlm.nih.gov/pubmed/29501875 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neuroimage.2018.02.062 |
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