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Abstract #3323

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

1 Department of Electronic Engineering, Tsinghua University, Beijing, Beijing, China, 2 MedImageMetric, LLC, New York, NY, United States, 3 Department of Automation, Tsinghua University, Beijing, Beijing, China, 4 Department of Radiology, Weill Medical College of Cornell University, New York, NY, United States, 5 Department 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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