A compressive sensing approach for enhancing breast cancer detection using a hybrid DBT/NRI configuration

Abstract

This work presents a novel breast cancer imaging approach that uses compressive sensing in a hybrid digital breast tomosynthesis (DBT)/nearfield radar imaging (NRI) system configuration. The non-homogeneous tissue distribution of the breast, described in terms of dielectric constant and conductivity, is extracted from the DBT image, and it is used by a full-wave finite difference in the frequency domain method to build a linearized model of the non-linear NRI imaging problem. The inversion of the linear problem is solved using compressive sensing imaging techniques, which lead to a reduction on the required number of sensing antennas and operational bandwidth without loss of performance.