MUSIC: Multi-Coil Unified Sparsity Regularization Using Inter-Slice Correlation for ASL MRI Denoising

Motivation: Signal-to-noise ratio (SNR) is relatively low in arterial spin labeling (ASL) MRI, particularly for high resolution, long post-labeling-delay, or long TE acquisitions. Goal(s): Increase ASL MRI SNR by leveraging data correlations among multi-channel data. Approach: Multi-coil Unified Sparsity regularization using Inter-slice Correlation (MUSIC) dynamically suppresses noise by exploiting low-rank properties of inter-slice correlations across channels. Results: Experimental validation on real-world imaging data demonstrates the efficacy of MUSIC in significantly enhancing ASL perfusion quality compared to existing methods. Impact: MUSIC enables more accurate perfusion imaging, potentially benefiting neuroimaging diagnostics and encouraging further research into SNR enhancement methods that refine non-invasive imaging across clinical and research settings.