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Abstract #0684

BladeNet: Rapid PROPELLER Acquisition and Reconstruction for High spatio-temporal Resolution Abdominal MRI

Efrat Shimron1, Alfredo De Goyeneche1, Ke Wang1, Alma Halgren1, Ali B. Syed2, Shreyas Vasanawala2, and Michael Lustig1
1UC Berkeley, Berkeley, CA, United States, 2Stanford, Stanford, CA, United States


To improve bowel wall imaging in abdominal pediatric MRI scans, we propose a multi-phase single-shot fast spin echo (SSFSE) PROPELLER acquisition with novel deep learning reconstruction. This acquisition offers shorter scan time and thus higher temporal resolution, PROPELLER built-in motion correction, and alias-free images; these however exhibit spatial blurring. Our approach leverages the blurring-axis temporal rotation and data redundancy; we train a network to recover high-frequency spatial details from consecutive frames. Retrospective simulations with data from balanced SSFP scans show that this approach yields reconstructions with high spatio-temporal resolution and motion-correction, which are essential for pediatric abdominal imaging.

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