Cancer Detection in Highly Dense Breasts Using Coherently Focused Time-Reversal Microwave Imaging

Abstract

Detection of tumors in highly dense breasts is a critical but challenging issue for early-stage breast cancer detection. We present the application of coherent focusing for time-reversal (TR) microwave imaging in beamspace for the detection and localization of multiple tumors in highly dense 3-D breast phantoms. We propose a novel coherent beamspace time reversal maximum likelihood (C-B-TR-ML) technique to obtain accurate tumor locations with reduced computational burden. To compare the performance, the coherent beamspace processing is also extended for conventional decomposition of the TR operator (DORT) and TR-MUSIC algorithms. A novel hybrid technique involving time of arrival and entropy is also proposed for early-time artifact removal as well as for estimating the Green's function of an equivalent virtual medium required for the TR operation. Finite-difference time-domain computations on anatomically realistic 3-D numerical breast phantoms are used to obtain the backscattered data. The results demonstrate the superior capabilities of the proposed C-B-TR-ML microwave-imaging technique in detecting and localizing multiple tumors embedded inside highly dense breast phantoms.