Fast reconstruction of SMS bSSFP myocardial perfusion images using a combination of parallel imaging and AI-based denoising

Simultaneous multi-slice (SMS) imaging enables high spatial coverage and resolution for myocardial perfusion imaging. We developed and evaluated a fast, noise-removing and signal-preserving SMS reconstruction approach combining parallel imaging and deep-learning and evaluated its benefit for myocardial perfusion imaging. In comparison to conventional parallel imaging reconstruction, the proposed SMS reconstruction provides improved perceived SNR and image quality (p<0.008), preserved sharpness and signal fidelity (p>0.05) in a short computation time (+20s for an entire dataset).