Ultrafast magnetic resonance spectroscopic imaging using SPICE with learned subspaces.

ABSTRACT:

Purpose

To develop a subspace learning method for the recently proposed subspace-based MRSI approach known as SPICE, and achieve ultrafast ¹ H-MRSI of the brain.

Theory and methods

A novel strategy is formulated to learn a low-dimensional subspace representation of MR spectra from specially acquired training data and use the learned subspace for general MRSI experiments. Specifically, the subspace learning problem is formulated as learning "empirical" distributions of molecule-specific spectral parameters (e.g., concentrations, lineshapes, and frequency shifts) by integrating physics-based model and the training data. The learned spectral parameters and quantum mechanical simulation basis can then be combined to construct acquisition-specific subspace for spatiosp

SUBMITTER: Lam F 

PROVIDER: S-EPMC6824949 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature