Whole Brain Susceptibility Mapping Using Harmonic Incompatibility Removal

TL;DR

This paper introduces a novel regularization method for quantitative susceptibility mapping that effectively addresses harmonic incompatibility in the data, improving the accuracy of susceptibility reconstructions.

Contribution

The paper reveals the inherent harmonic incompatibility in QSM data acquisition and proposes a new regularization model incorporating sparsity on this incompatibility for enhanced reconstruction.

Findings

Outperforms existing QSM reconstruction methods

Addresses harmonic incompatibility in local field data

Improves susceptibility map accuracy

Abstract

Quantitative susceptibility mapping (QSM) aims to visualize the three dimensional susceptibility distribution by solving the field-to-source inverse problem using the phase data in magnetic resonance signal. However, the inverse problem is ill-posed since the Fourier transform of integral kernel has zeroes in the frequency domain. Although numerous regularization based models have been proposed to overcome this problem, the incompatibility in the field data has not received enough attention, which leads to deterioration of the recovery. In this paper, we show that the data acquisition process of QSM inherently generates a harmonic incompatibility in the measured local field. Based on such discovery, we propose a novel regularization based susceptibility reconstruction model with an additional sparsity based regularization term on the harmonic incompatibility. Numerical experiments show that the proposed method achieves better performance than the existing approaches.