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This article describes a microwave tomographic approach for the quantitative imaging of brain stroke inside the human head. For the acquisition of the scattered-field information, a prototype of multistatic system is adopted. An array of custom antennas is placed in contact with the head, and a switching matrix is used to measure the scattering parameters for each pair of probes. The collected data are processed by an inversion method based on a variable-exponent Lebesgue-space regularization technique, whose outcome is a map of dielectric properties of a slice of the head. With respect to previous approaches, this kind of inversion procedure performs an adaptive update of the Lebesgue-space exponents on the basis of the results at each inexact-Newton iteration and exploits stepped frequency data. This allows for an automatic setting of the regularization level, which becomes variable and target-dependent inside the whole investigation domain. The proposed approach is validated by means of FDTD synthetic simulations with a realistic 3-D forward scattering model of the human head, as well as by using real experimental cylindrical test phantoms filled with saline and glycerin/water mixtures. [ABSTRACT FROM AUTHOR]

A conjugate-gradient-based regularization technique in $L^{p}$ Banach spaces, in conjunction with an inexact-Newton solving scheme, is presented in this paper. The proposed method is applied to obtain the reconstruction of the dielectric properties of human tissues in hemorrhagic brain stroke microwave imaging. The dielectric reconstruction is obtained by solving a nonlinear inverse problem, starting from a set of scattered-field measurements. The presented numerical simulations with 2-D and 3-D anatomically realistic phantoms, as well as the preliminary experimental results, show that this method can be useful for retrieving the dielectric properties of the human head with a reduced over-smoothing effect in the final images. [ABSTRACT FROM AUTHOR]