Quantitative microwave holography is a recent imaging methodology that shows promise in medical diagnostics. It is a real-time direct inversion algorithm that reconstructs the complex permittivity from S-parameter measurements on an acquisition surface outside of the imaged object. It is recognized that this imaging method suffers from limitations in tissue imaging due to a forward model which linearizes a highly nonlinear scattering problem. It is therefore important to study its limitations when reconstruction is aided by certain pre-and post-processing filters which are known to improve the image quality. The impact of filtering on the quantitative result is particularly important. In this work, the reconstruction equations of quantitative microwave holography are derived from first principles. The implementation of two linearizations strategies, Born's approximation and Rytov's approximation, is explained in detail in the case of a scattering model formulated in terms of S-parameters. Furthermore, real-space and Fourier-space filters are developed to achieve the best performance for the given linearized model of scattering. Simulated and experimental results demonstrate the limitations of the method and the necessity of filtering. The two approximations are also compared in experimental tissue reconstructions.

Abstract-A novel TEM horn antenna placed in a solid dielectric medium is proposed for microwave imaging of the breast. The major design requirement is that the antenna couples the microwave energy into the tissue without being immersed itself in a coupling medium. The antenna achieves this requirement by: 1) directing all radiated power through its front aperture, and 2) blocking external electromagnetic interference by a carefully designed enclosure consisting of copper sheets and power absorbing sheets. In the whole ultra-wide band the antenna features: 1) good impedance match, 2) uniform field distribution at the antenna aperture, and 3) good coupling efficiency.

Abstract-We present a novel approach for adjoint transient sensitivity analysis with respect to discontinuities with spacedependent materials exhibiting known distribution. Our approach integrates the Time Domain Transmission-Line-Modeling (TD-TLM) with the Adjoint Variable Method (AVM). Using only one extra TD-TLM simulation, the sensitivities of the observed response with respect to all the parameters of the Gaussian distribution are obtained. The accuracy of our sensitivity analysis approach is illustrated through a number of different 2D and 3D examples. Using the previous sensitivities, gradient-based optimization technique is applied to exploit in the location and profile of various inhomogeneous material Gaussian distribution for inverse problems. This method can be repeated for any continuous or discontinuous distributions that exist in electromagnetic imaging for space dependent materials like cancer detection.