Partial fourier and parallel MR image reconstruction with integrated gradient nonlinearity correction.

ABSTRACT:

Purpose

To describe how integrated gradient nonlinearity (GNL) correction can be used within noniterative partial Fourier (homodyne) and parallel (SENSE and GRAPPA) MR image reconstruction strategies, and demonstrate that performing GNL correction during, rather than after, these routines mitigates the image blurring and resolution loss caused by postreconstruction image domain based GNL correction.

Methods

Starting from partial Fourier and parallel magnetic resonance imaging signal models that explicitly account for GNL, noniterative image reconstruction strategies for each accelerated acquisition technique are derived under the same core mathematical assumptions as their standard counterparts. A series of phantom and in vivo experiments on retrospectively undersampled data

SUBMITTER: Tao S 

PROVIDER: S-EPMC4716004 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature