Simultaneous multi-slice (SMS) acquisitions enable higher resolutions to be achieved for arterial spin labelling (ASL) images. However, SMS acquisitions can introduce a banded pattern of intensity within the images. This reduces the quality of motion estimation as the algorithm aligns the bands in preference to the brain structures. We introduce a Gaussian Process model that can be used to correct the banding in SMS multiple post-labelling delay ASL data, which should improve motion correction. We demonstrate its effectiveness on 10 subjects from the Human Connectome Project Aging dataset. We anticipate that the model will generalise to other ASL datasets.
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