Hybrid data fidelity term approach for quantitative susceptibility mapping.

ABSTRACT:

Purpose

Susceptibility maps are usually derived from local magnetic field estimations by minimizing a functional composed of a data consistency term and a regularization term. The data-consistency term measures the difference between the desired solution and the measured data using typically the L2-norm. It has been proposed to replace this L2-norm with the L1-norm, due to its robustness to outliers and reduction of streaking artifacts arising from highly noisy or strongly perturbed regions. However, in regions with high SNR, the L1-norm yields a suboptimal denoising performance. In this work, we present a hybrid data fidelity approach that uses the L1-norm and subsequently the L2-norm to exploit the strengths of both norms.

Methods

We developed a hybrid data fidelity term a

SUBMITTER: Lambert M 

PROVIDER: S-EPMC9324845 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature