In this paper, an innovative microwave imaging (MI) approach for breast tumor diagnosis is proposed that employs a differential formulation of the inverse scattering problem (ISP) at hand to exploit arbitrary-fidelity priors on the inhomogeneous reference/healthy tissues. The quantitative imaging of the unknown tumor is then rephrased into a global optimization problem, which is efficiently solved with an ad-hoc physics-driven artificial intelligence (AI) strategy inspired by the concepts and guidelines of the System-by-Design (SbD) paradigm. The effectiveness, the robustness, the reliability, and the efficiency of the proposed method are assessed against both synthetic and experimental data.
@article{arxiv.2401.02715,
title = {A Physics-Driven AI Approach for Microwave Imaging of Breast Tumors},
author = {Francesco Zardi and Luca Tosi and Marco Salucci and Andrea Massa},
journal= {arXiv preprint arXiv:2401.02715},
year = {2024}
}