Eigenvector-based SPIRiT Parallel MR Imaging Reconstruction based on ℓp pseudo-norm Joint Total Variation

Publication date: Available online 25 January 2019

Source: Magnetic Resonance Imaging

Author(s): Jizhong Duan, Zhongwen Bao, Yu Liu

Abstract

Parallel Magnetic Resonance (MR) imaging is a well-established acceleration technique based on the spatial sensitivities of array receivers. Eigenvector-based SPIRiT (ESPIRiT) is a new parallel MR imaging reconstruction method that combines the advantages of the SENSE and GRAPPA methods. It estimates multiple sets of the sensitivity maps from the calibration matrix that is constructed from the auto-calibration data. To improve the quality of the reconstructed image, we introduced the Total Variation (TV) and ℓ_p pseudo-norm Joint TV (ℓ_pJTV) regularization terms to the ESPIRiT model for parallel MR imaging reconstruction, which were solved by using the Operator Splitting (OS) method. The resulting denoising problems with the TV and ℓ_pJTV regularization terms were solved by exploiting the majorization minimization method. Simulation experiments on two in vivo data sets demonstrated that the proposed OS algorithm with the TV regularization term (OSTV) and OS algorithm with the ℓ_pJTV regularization term (OSℓ_pJTV) outperformed the conventional method with the ℓ₁ regularization term in terms of SNR and NRMSE. And the OSℓ_pJTV algorithm was slightly superior to the OSTV algorithm with the TV regularization term.

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