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

Research output: Contribution to journalArticle


Purpose: To present a general and efficient method for macroscopic intravoxel R* 2 inhomogeneity corrected reconstruction from multi-TE acquisitions. Theory and Methods: A signal encoding model for multi-TE gradient echo (GRE) acquisitions that incorporates 3D intravoxel R* 2 field variations is derived, and a low-rank approximation to the encoding operator is introduced under piecewise linear R* 2 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. Results: Experimental multi-echo GRE data were acquired to evaluate the proposed method. Effective reduction of macroscopic intravoxel R* 2 inhomogeneity induced artifacts was demonstrated. Improved R* 2 estimation from the corrected reconstruction over standard Fourier reconstruction has also been obtained. Conclusions: The proposed method can effectively correct the effects of intravoxel R* 2 inhomogeneity, and can be useful for various imaging applications involving GRE-based acquisitions, including fMRI, quantitative R* 2 and susceptibility mapping, and MR spectroscopic imaging.

Original languageEnglish (US)
JournalMagnetic Resonance in Medicine
StateAccepted/In press - Jan 1 2020


  • image reconstruction
  • inhomogeneity correction
  • intravoxel inhomogeneity
  • low-rank models
  • multi-echo acquisitions

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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