Abstract :
Based on the finite-difference time-domain (FDTD) method, a numerical time-reversal (TR) algorithm for microwave breast cancer detection, already presented in previous work , , is further examined. In , we assumed that the exact field scattered from the tumor-like anomaly is available for backpropagation, and it was shown that the time reversal process is robust to breast inhomogeneities and uncertainties of the skin thickness or electric properties. In this paper, we use the same time reversal mirror (TRM) and two-dimensional (2-D) breast model based on magnetic resonance imaging (MRI) data, but examine the realistic situation where the target response is not known and can only be estimated from the total signal, which is dominated by clutter. A matched-filter approach to solve this signal processing problem is proposed and applied to the TRM data. Detection and localization is achieved for different target locations, and the ability of the time reversal algorithm to avoid false alarms is demonstrated.
Keywords :
biomedical MRI; cancer; clutter; finite difference time-domain analysis; matched filters; microwave imaging; FDTD; MRI; TRM; breast cancer detection; clutter; finite difference time domain; magnetic resonance imaging data; matched-filter approach; microwave imaging; signal processing problem; target detection; target localization; time reversal mirror; two-dimensional breast model; Backpropagation algorithms; Breast cancer; Cancer detection; Finite difference methods; Magnetic resonance imaging; Microwave theory and techniques; Scattering; Signal processing algorithms; Time domain analysis; Transmission line measurements; Breast cancer detection; finite-difference time-domain (FDTD); matched-filter; microwave imaging; time reversal;
