Rapid T₁ quantification from high resolution 3D data with model-based reconstruction.

ABSTRACT:

Purpose

Magnetic resonance imaging protocols for the assessment of quantitative information suffer from long acquisition times since multiple measurements in a parametric dimension are required. To facilitate the clinical applicability, accelerating the acquisition is of high importance. To this end, we propose a model-based optimization framework in conjunction with undersampling 3D radial stack-of-stars data.

Theory and methods

High resolution 3D T₁ maps are generated from subsampled data by employing model-based reconstruction combined with a regularization functional, coupling information from the spatial and parametric dimension, to exploit redundancies in the acquired parameter encodings and across parameter maps. To cope with the resulting non-linear, non-d

SUBMITTER: Maier O 

PROVIDER: S-EPMC6588000 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature