A Fast Algorithm for Microwave Biomedical Imaging with Inhomogeneous Background

This paper presents a fast and robust algorithm for solving microwave biomedical imaging problems, which are typically modelled as the reconstruction of unknown targets that are embedded in an inhomogeneous background. We treat inhomogeneous background as a known scatterer, which has the advantage of avoiding the time-consuming calculation of inhomogeneous background Green's function. Under this scheme, we propose two difference integral equation models, i.e., difference Lippmann-Schwinger integral equation (D-LSIE) and difference new-type integral equation (D-NIE). The two models are shown to run fast and be able to reconstruct scatterers with high contrast with respect to background. The proposed algorithm is validated by an imaging problem for a human thorax model.