Files

Abstract

In this work we investigate the combination of Model-based Accelerated RelaxomeTry by Iterative Nonlinear Inversion (MARTINI) with Generalized Autocalibrating Partially Parallel Acquisition (GRAPPA) to further accelerate and improve the reconstruction quality of T2 maps. GRAPPA is used to interpolate missing k-space lines of two-fold subsampled blocks of the MARTINI scheme prior to the MARTINI reconstruction. Images from an analytical phantom and in-vivo datasets are investigated. Resulting T2 maps of nominal 10-fold accelerated whole brain exams (1:40 minutes scans) are qualitatively and quantitatively compared to the reconstruction of the fully sampled and conventional 5-fold accelerated MARTINI datasets.

Details

Actions

Preview