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...
| Hlavní autoři: | , , |
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| Médium: | Journal article |
| Jazyk: | English |
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Elsevier
2018
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