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Abstract #1834

Sliding-Window-Based Frame Selection for T1-Mapping GOAL-SNAP MRA

Haokun Li1, Jiaqi Dou1, Xiaoming Liu2, Haozhong Sun1, and Huijun Chen1
1Center for Biomedical Imaging Research, School of Biomedical Engineering, Tsinghua University, Beijing, China, 2Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

Synopsis

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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Keywords