Dynamic arterial spin labeling MRI provides important quantitative information about blood arrival time and perfusion. However, the inherently low signal-to-noise ratio requires repeated measurements to achieve a reasonable image quality. This leads to long acquisition times and hence increases the risk of motion artifacts, which impedes clinical applicability. To overcome this limitation we propose to reconstruct the dynamic ASL data employing ICTGV regularization from a reduced number of averages. The performance of the method is evaluated on synthetic and in-vivo ASL data.
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