SPIRiT: Iterative self-consistent parallel imaging reconstruction from arbitrary k-space.

Abstract:

:A new approach to autocalibrating, coil-by-coil parallel imaging reconstruction, is presented. It is a generalized reconstruction framework based on self-consistency. The reconstruction problem is formulated as an optimization that yields the most consistent solution with the calibration and acquisition data. The approach is general and can accurately reconstruct images from arbitrary k-space sampling patterns. The formulation can flexibly incorporate additional image priors such as off-resonance correction and regularization terms that appear in compressed sensing. Several iterative strategies to solve the posed reconstruction problem in both image and k-space domain are presented. These are based on a projection over convex sets and conjugate gradient algorithms. Phantom and in vivo studies demonstrate efficient reconstructions from undersampled Cartesian and spiral trajectories. Reconstructions that include off-resonance correction and nonlinear l(1)-wavelet regularization are also demonstrated.

journal_name

Magn Reson Med

authors

Lustig M,Pauly JM

doi

10.1002/mrm.22428

subject

Has Abstract

pub_date

2010-08-01 00:00:00

pages

457-71

issue

2

eissn

0740-3194

issn

1522-2594

journal_volume

64

pub_type

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