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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