Expand description
HD-QSM: Hybrid data-fidelity two-stage linear dipole inversion.
A linear dipole-inversion method that runs in two stages. Stage 1 solves an L1 data-fidelity problem (robust to phase/model errors) and derives a spatially-varying discrepancy weighting. Stage 2 solves an L2 data-fidelity problem reweighted by that discrepancy map. Both stages use ADMM with an L1 total-variation regularizer.
Because the whole method is linear and scale-consistent, feed the local field in ppm directly and the output susceptibility is in ppm as well (no phase scaling required).
Reference: Lambert, M., Tejos, C., Langkammer, C., et al. (2022). “Hybrid data fidelity term approach for quantitative susceptibility mapping.” Magnetic Resonance in Medicine, 87(6):3059-3072. https://doi.org/10.1002/mrm.29218
Reference implementation: HDQSM.m, https://github.com/mglambert/HD-QSM (MIT).
Structs§
- HdQsm
Params - HD-QSM algorithm parameters.
Functions§
- apply_
dipole 🔒 - Forward dipole convolution:
Dx = real(ifft(kernel .* fft(x))). - hdqsm
- HD-QSM dipole inversion.
- norm2 🔒
- L2 norm of a slice.
- percent_
update 🔒 - Percent update
100 * ||x - x_prev|| / ||x||.