Arterial spin labeling (ASL) perfusion fMRI has much less neurovascular effects than BOLD fMRI, but its application in time-series analysis is still depreciated due to the low signal-to-noise-ratio (SNR). In this study, we propose a patch based low rank and sparse decomposition method to denoise ASL MRI. Our results showed that the proposed method can markedly increase the sensitivity of ASL MRI-based task activation detection.
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