Keywords: Image Reconstruction, Vessels
Motivation: The development of MRA using the GOAL-SNAP sequence offers significant advantages, such as generating automatically registered T1-Mapping and MRA images. However, existing GOAL-SNAP MRA techniques still present opportunities for further enhancement.
Goal(s): To develop an approach to further optimize GOAL-SNAP MRA.
Approach: A sliding-window based frame searching method is utilized to find the optimal group of spokes for the reconstruction of GOAL-SNAP MRA.
Results: Qualitative and quantitative metrics have demonstrated the superiority of our method in terms of contrast between large vessels and white matter and distal vessel visibility. Results also show that GOAL-SNAP MRA performs better than TOF in stenosis severity estimation.
Impact: A novel sliding-window-based frame searching method enhances GOAL-SNAP MRA for improved visualization of intracranial vessels. The proposed method demonstrates superior performance in visualizing distal vessels and estimating the severity of stenosis compared to TOF MRA.
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