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Abstract #2452

Density compensation for iterative reconstruction from under-sampled radial data

Boris Mailhe 1 , Qiu Wang 1 , Robert Grimm 2 , Marcel Dominik Nickel 2 , Kai Tobias Block 3 , Hersh Chandarana 3 , and Mariappan S. Nadar 1

1 Imaging and Computer Vision, Siemens Corporation, Corporate Technology, Princeton, NJ, United States, 2 MR Application & Workflow Development, Siemens Healthcare, Erlangen, Germany, 3 Department of Radiology, New York University School of Medicine, New York, NY, United States

Density compensation is a mandatory step for direct reconstruction of radial MRI data. We interpret density compensation as a left-hand-side preconditioner of the measurement operator. We propose an alternative formulation as a right-hand-side preconditioner compatible with regularized iterative reconstruction. In the case of under-sampled radial trajectories, we show that a ramp filter overemphasizes high frequencies. Instead, we calibrate the preconditioner offline. We show that preconditioning accelerates the reconstruction and improves the sharpness of the reconstructed images.

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