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Abstract #1961

Primal-Dual Implementation for Quantitative Susceptibility Mapping (QSM)

Youngwook Kee1, Kofi Deh1, Alexey Dimov1,2, Pascal Spincemaille1, and Yi Wang1,2

1Weill Cornell Medical College, New York, NY, United States, 2Cornell University, Ithaca, NY, United States

We investigate the computational aspects of the prior term in the field-to-susceptibility inversion problem for QSM. Providing a spatially continuous formulation of the problem, we analyze 1) its Euler-Lagrange equation that appears degeneracy and 2) the Gauss-Newton conjugate gradient (GNCG) algorithm that employs numerical conditioning. We propose a primal-dual (PD) formulation that avoids such degeneracy and use the Chambolle-Pock algorithm to solve this alternative formulation; thus numerical conditioning is not required. The two methods were tested and validated on numerical/gadolinium phantoms and ex-vivo/in-vivo MRI data. The PD formulation with the Chambolle-Pock algorithm was faster and more accurate than GNCG.

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