Distribution Specified Dipole Inversion for Quantitative Susceptibility Mapping
Yilin Yang 1 , Tian Liu 2 , Jianwu Dong 3 , Pascal Spincemaille 4 , and Yi Wang 4,5
Department of Electronic Engineering,
Tsinghua University, Beijing, Beijing, China,
LLC, New York, NY, United States,
of Automation, Tsinghua University, Beijing, Beijing,
of Radiology, Weill Medical College of Cornell
University, New York, NY, United States,
of Biomedical Engineering, Cornell University, Ithaca,
NY, United States
Dipole inversion is the final step of the QSM algorithm.
In this step, the zero cone surface in the dipole kernel
makes the field-to-susceptibility inverse problem
ill-posed. Current solutions are mostly based on the
Bayesian approach. Previous techniques have used
weighted L1-norm with binary weights derived from the
gradient echo magnitude image or phase image. Taking the
information from the distribution of the susceptibility
gradient into account could improve the reconstructed
image. And L2-norm converges faster than L1-norm.
Therefore, we employ reweighted L2-norm to specify the
distribution to Gaussian. The results of this novel
Distribution Specified Dipole Inversion (DSDI) method
demonstrate an enhancement of QSM reconstruction and a
significant shortening in calculation time.
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