Application of Spectral Approach Combined with U-NETs for Quantitative Microwave Breast Imaging.

This study focuses on breast imaging. A spectral approach based on the Fourier diffraction theorem is combined with a pair of U-NETs to perform real-time quantitative human breast imaging. The U-NET pair is trained based on the input of an induced current spectrum and the output of a contrast dielectric spectrum. A spectral database is constructed using combinations of anthropomorphic cavities. The weighted mean absolute percentage error (WMAPE) loss is associated with the Adam optimizer to perform optimization. Numerical results are presented to validate the proposed concept to demonstrate the transformation brought about by the U-NETs.