3D GRASE (GRAdient and Spin Echo) pulse sequence has been widely employed as the readout in arterial spin labeling (ASL) applications, given its efficient acquisition and relatively long lasting signal intensities. However, the inherent weakness of GRASE, such as vulnerability to motions, can induce ghosting artifacts to perfusion imaging and quantitative cerebral blood perfusion (CBF) maps. Herein, we propose applying the Multi-Dimensional Integration (MDI) algorithm to processing the perfusion and CBF maps, by which method noticeable alleviation of motion ghosting can be obtained, and the imaging noise is reduced as well.
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