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Abstract #1919

Advancing 3T Vessel Wall Imaging through Combined Deep Learning Acceleration and Reconstruction for Rapid, High-Resolution Scans

Xiaoqian Zhang1, Yifei Zhang2, Meiling Liu2, Hui You1, Mingli Li1, and Feng Feng1
1Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China, 2GE Healthcare, Beijing, China

Synopsis

Keywords: Blood Vessels, Vessel Wall

Motivation: Achieving high-resolution vessel wall imaging (VWI) within a clinically feasible scan time remains challenge.




Goal(s): We aimed to combine deep learning (DL) techniques to reduce scan times and improve image quality, enabling both rapid routine imaging and high-resolution VWI.


Approach: A 3T MRI was used with DL acceleration and DL reconstruction to perform black blood T1-weighted imaging at 0.7 mm and 0.4 mm isotropic resolutions.




Results: The combined DL techniques allowed for 0.7 mm resolution scans in under 2 minutes and 0.4 mm resolution scans in 7.5 minutes, achieving diagnostically acceptable quality and pushing resolution boundaries.




Impact: This study demonstrates the feasibility of combining two DL techniques for rapid and high-resolution vessel wall imaging, offering unprecedented quality and speed at 3T. This approach also provides insights for applying DL methods in other challenging imaging sequences.

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