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In this paper, an innovative microwave imaging (MI) approach for breast tumordiagnosis is proposed that employs a differential formulation of the inversescattering problem (ISP) at hand to exploit arbitrary-fidelity priors on theinhomogeneous reference/healthy tissues. The quantitative imaging of theunknown tumor is then rephrased into a global optimization problem, which isefficiently 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 theefficiency of the proposed method are assessed against both synthetic andexperimental data.

A Physics-Driven AI Approach for Microwave Imaging of Breast Tumors