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Abstract #2265

On Density Compensation in Bayesian K-Space Trajectory Optimization

Jan Aelterman1, Hiep Luong1, Bart Goossens1, Aleksandra Pizurica1, Wilfried Philips1

1TELIN-IPI-IBBT, Ghent University, Ghent, Belgium

It is demonstrated that trajectory optimization is of crucial importance in compressed sensing MRI reconstruction. Variational Bayesian k-space trajectory optimization techniques is then analyzed from the point of view of variable density k-space sampling. It is shown that density compensation is imperative in this framework and we present new and computationally very efficient method to estimate the density compensation function.