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Abstract #1761

Real-Time Spiral bSSFP Functional Cardiac MRI on a 0.55T Scanner Using a Deep Image Prior Reconstruction with GROG

Jesse Ian Hamilton1,2 and Nicole Seiberlich1,2
1Radiology, University of Michigan, Ann Arbor, MI, United States, 2Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States


This work introduces a physics-based deep learning reconstruction that can enable real-time (free-breathing and ungated) spiral 2D bSSFP functional cardiac MRI on a 0.55T scanner. The proposed method extends the concept of a deep image prior and does not require prior training on reference data. In addition, GROG is used to reduce the computational complexity of the forward model calculation by shifting spiral k-space data to their nearest Cartesian grid points, allowing use of FFT rather than NUFFT operations. Results are demonstrated in healthy subjects with functional measurements compared to gold standard acquisitions at 1.5T.

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