Keywords: Arterial Spin Labelling, Perfusion, arterial transit time
Motivation: Arterial transit time (ATT) is a quantity of increasing clinical interest for understanding neurovascular health. ATT may be measured using multi-delay arterial spin labelling (ASL), but due to the low signal to noise ratio and non-linear kinetics of this imaging technique, obtaining accurate and robust measurements can be challenging.
Goal(s): To better estimate arterial transit time from multiple-delay arterial spin labelling data.
Approach: Model-fitting via stochastic variational Bayesian inference with joint spatial and non-spatial prior regularisation.
Results: The new method is more robust than existing methods on noisy data, and produces maps with greater anatomical detail on acquisition data.
Impact: The advantages of this new method will enable researchers to better exploit ATT measurement via multi-delay ASL, furthering understanding of neurovascular health.
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