Intravoxel B0 inhomogeneity corrected reconstruction using a low-rank encoding operator.

Abstract

To present a general and efficient method for macroscopic intravoxel inhomogeneity corrected reconstruction from multi-TE acquisitions. A signal encoding model for multi-TE gradient echo (GRE) acquisitions that incorporates 3D intravoxel field variations is derived, and a low-rank approximation to the encoding operator is introduced under piecewise linear assumption. The low-rank approximation enables very efficient computation and memory usage, and allows the proposed signal model to be integrated into general inverse problem formulations that are compatible with multi-coil and undersampling acquisitions as well as different regularization functions. Experimental multi-echo GRE data were acquired to evaluate the proposed method. Effective reduction of macroscopic intravoxel inhomogeneity induced artifacts was demonstrated. Improved estimation from the corrected reconstruction over standard Fourier reconstruction has also been obtained. The proposed method can effectively correct the effects of intravoxel inhomogeneity, and can be useful for various imaging applications involving GRE-based acquisitions, including fMRI, quantitative and susceptibility mapping, and MR spectroscopic imaging.