Field-Based Discretization of the 3-D Contrast Source Inversion Method Applied to Brain Stroke Microwave Imaging

The contrast source inversion method is an iterative non-linear algorithm, and, in this paper, it works in combination with a finite element method solver for the reconstruction of the dielectric properties' distribution in the head with the aim to diagnose brain stroke. Here, the involved contrast source variables are discretized through a novel field-based discretization that allows a linear variation of the variables, leading to their more accurate description, and therefore to a final dielectric properties' reconstruction closer to the expected scenario. Moreover, we propose a new approach to compute the imaging algorithm initial guess, based on the truncated singular value decomposition technique, that appears more effective in the case of noisy measured data. Finally, the developed algorithm is applied to sets of data, measured with a microwave imaging system to reconstruct brain stroke scenarios.