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Abstract #3710

Improved Compressed Sensing Reconstructions with MOET

Daniel Neumann1, Felix A. Breuer1, Peter M. Jakob1, 2, Mark A. Griswold3, 4

1Research Center MR Bavaria (MRB), Wrzburg, Germany; 2Experimental Physics 5, University of Wrzburg, Wrzburg, Germany; 3Radiology, University Hospitals, Cleveland, OH, United States; 4Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States

MOET is a 2D sampling scheme based on radial sampling combined with oscillating gradients providing incoherent aliasing artifacts. This is essential to the success of Compressed Sensing algorithms. Real-time in-vivo cardiac data along a MOET and a standard radial trajectory were acquired and reconstructed using CS exploiting sparsity in the frequency domain with a temporal resolution of 51.2ms per frame. The reconstructed MOET images exhibit an overall improved image quality with fewer residual aliasing artifacts compared to the radial trajectory.