Abstract #3670

Effect of Poisson kernel parameters on background field removal accuracy for QSM

Debra E. Horng^1,2, Samir D. Sharma¹, Scott B. Reeder^1,2,3,4,5, and Diego Hernando^1,2

¹Radiology, University of Wisconsin, Madison, WI, United States, ²Medical Physics, University of Wisconsin, Madison, WI, United States, ³Biomedical Engineering, University of Wisconsin, Madison, WI, United States, ⁴Medicine, University of Wisconsin, Madison, WI, United States, ⁵Emergency Medicine, University of Wisconsin, Madison, WI, United States

The Poisson Estimation for Ascertaining Local fields (PEAL) kernel is a recently-introduced method for background field removal in quantitative susceptibility mapping (QSM). The PEAL kernel is determined by two parameters: radius and spatial shift. The choice of these two parameters may have a substantial effect on the accuracy of background field removal. In this work, we assessed the effect of PEAL kernel size and shift on the accuracy of background field removal and susceptibility estimation.

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