Keywords: Image Reconstruction, Vessels
Motivation: GOAL-SNAP, a sequence designed for T1 value measurement of vessel walls, shows promise in generating MRA images for intracranial vessel visualization, albeit with opportunities for further improvement.
Goal(s): To introduce a novel approach to optimize GOAL-SNAP MRA.
Approach: A histogram-matching-based approach was developed to optimize GOAL-SNAP MRA. This technique combined multiple GOAL-SNAP frames and utilizes histogram matching to suppress background signals and improve the contrast between vessels and background.
Results: Contrast-to-noise (CNR) and visualization evaluation demonstrated the effectiveness of the optimized GOAL-SNAP MRA, exhibiting comparable performance to TOF and superior visualization of distal vessels.
Impact: A novel histogram-matching-based multi-frame combination approach improved GOAL-SNAP MRA for intracranial vessel visualization and vascular stenosis assessment, with comparable performance to TOF and superior visualization of distal vessels.
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