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Abstract #2730

Dynamically Regularized TSENSE Improves Image Quality in Parallel MRI

Martin Blaimer1, Felix A. Breuer1, Peter M. Jakob1, Mark A. Griswold2, Peter Kellman3

1Research Center Magnetic Resonance Bavaria (MRB), Wrzburg, Bavaria, Germany; 2Department of Radiology, University Hospitals of Cleveland and Case Western Reserve University, Cleveland, OH, USA; 3Laboratory of Cardiac Energetics, National Institutes of Health, National Heart, Lung and Blood Institute, Bethesda, MD, USA

The proposed dynamic regularized TSENSE parallel MRI method improves image quality by utilizing temporal signal correlations. Parallel MRI is applied only to the dynamic portion of the signal as determined by changes from the temporal average, also using the signal change for regularizing the solution. A first pass estimate with full temporal and spatial resolution is derived using the TGRAPPA method without the requirement for separate training data. The full resolution estimate is used for dynamic regularized SENSE reconstruction after removal of the temporal average (DC term) and SNR based regularization uses the difference between the current and the temporal average image.