A fast, effective filtering method for improving clinical pulsed arterial spin labeling MRI.

Purpose: To evaluate the effectiveness of a fully automated postprocessing filter algorithm in pulsed arterial spin labeling (PASL) MRI perfusion images in a large clinical population.

Materials And Methods: A mean and standard deviation-based filter was implemented to remove outliers in the set of perfusion-weighted images (control - label) before being averaged and scaled to quantitative cerebral blood flow (CBF) maps. Filtered and unfiltered CBF maps from 200 randomly selected clinical cases were assessed by four blinded raters to evaluate the effectiveness of the filter.