Keywords: Arterial spin labelling, BrainTime-encoded Arterial Spin Labeling (teASL) enables time-efficient acquisition of multiple averages of multiple post-labeling-delay (PLD) perfusion-weighted images (PWIs). We developed a dedicated teASL reconstruction that employs Infimal Convolution of Total Generalized Variation (ICTGV) regularization directly on the PWIs. Using simulated and healthy volunteer data, the ICTGV reconstruction produced inherently denoised images and improved cerebral blood flow and arterial transit time maps compared to a SENSE reconstruction. Also, for an 8-fold accelerated in-vivo dataset, the ICTGV reconstruction still produced reasonable PWIs, which the SENSE reconstruction could not. Therefore, ICTGV reconstruction is promising for teASL and allows high acceleration with inherent denoising.
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