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Abstract #4517

Generating 3D Volumetric Brain Images via Other Contrast Guidance from 2D Thick Slices

Long Wang1, Lei Xiang1, Ryan Chamberlain1, Xinyu Song2, Xiao-Er Wei2, and Yuehua Li2
1Subtle Medical, Menlo Park, CA, United States, 2Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China

Synopsis

Keywords: AI/ML Image Reconstruction, Multi-Contrast

Motivation: The conventional multiple sclerosis(MS) protocol in the brain normally takes from 30 minutes to several hours. It often involves multiple 3D series for the quantitative metrics and reports.

Goal(s): To reduce the scan time for the brain MS protocols with more than one 3D series

Approach: We proposed a framework that utilized a 3D T1 and 2D FLAIR as inputs to generate a 3D T2 FLAIR.

Results: The method generates comparable image resolution on all orientations as the acquired 3D FLAIR, and outperforms other methods. The lesion segmentation masks show high consistency. Furthermore, the method demonstrates robustness in the cases with motion.

Impact: The method provides the solution of generating a volumetric FLAIR using the same time as a 2D series and achieving comparable resolutions and diagnosis accuracy as the 3D FLAIR.

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Keywords