Quantitative Susceptibility Mapping for MRI part 2

Magnitude Weighted Quantitative Susceptibility Mapping.

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Efficient implementation of L1-regularized magnitude weighted QSM, proposed by B. Bilgic et al.
Here the susceptibility distribution is calculated that has an optimal balance between:
- explaining the measured field (minimal residual)
- a 'crisp' appareance: minimal Total Variation between neighbouring voxels, with inclusion of the magnitude data.
Based on the method proposed by Berkin Bilgic et al.
- his software: https://www.martinos.org/~berkin/software.html
- his paper: Berkin Bilgic, Audrey P. Fan,Jonathan R. Polimeni,Stephen F. Cauley, Marta Bianciardi, Elfar Adalsteinsson, Lawrence L. Wald and Kawin Setsompop; "Fast quantitative susceptibility mapping with L1-regularization and automatic parameter selection" Journal of Magnetic Resonance Imaging.
Please refer to this and the reference given below when using this script.

In this work a further fourfold reduction in the needed number of calculations is proposed by 1) buffer-free parameter sweeps, 2) a Half-Fourier L2-sweep, 3) a pairwise L1-sweep, and 4) performing the Split Bregman gradient operations in the spatial domain.
A detailed description on these adaptations is currently under review as an abstract, submitted to the ESMRMB 2015, Abstract ID: #911 (under review)
"Efficient optimally L1 regularized magnitude weighted QSM", Job G Bouwman, Peter R Seevinck.
Please refer to this and the reference given above when using this script.

Cite As

Job (2026). Quantitative Susceptibility Mapping for MRI part 2 (https://www.mathworks.com/matlabcentral/fileexchange/50940-quantitative-susceptibility-mapping-for-mri-part-2), MATLAB Central File Exchange. Retrieved .

General Information

MATLAB Release Compatibility

  • Compatible with any release

Platform Compatibility

  • Windows
  • macOS
  • Linux
Version Published Release Notes Action
1.1.0.0

minor details (textual, annotations, ..)

1.0.0.0