Near-Optimal Spatial Encoding for Dynamically Adaptive MRI: Mathematical Principles and Computational Methods

摘要

The mathematical principles of near-optimal two-dimen- sional spatial encoding for dynamically adaptive magnetic resonance imaging (MRI) are presented together with a survey of numerical methods applicable for the computation of these encodes. Two main classes of linear algebraic techniques are identified-rank revealing orthogonal decompositions and Krylov subspace methods-that are specially suited for the determination of efficient adaptive non-Fourier spatial encoding. Simulation results are presented to demonstrate usage.