UWB microwave imaging for breast cancer detection: tumor/clutter identification using a time of arrival data fusion method

This paper proposed a novel scheme for early breast cancer detection using UWB microwave imaging. By applying the CLEAN algorithm to process the received signals at each sensor, the IR components can be successfully resolved. The locations and scattering strengths of dominant scatterers are then estimated based on the TOA data fusion concept. Simulation results have indicated the feasibility of detecting a tumor of 2 mm at depth of 2 cm. As compared to the existing techniques, the proposed approach is more computationally-efficient since the scanning process is localized at a few candidate locations. A number of issues that need to be addressed in future include: (i) effectiveness of the proposed approach for 3-D phantoms with realistic breast shapes and tissue compositions; (ii) extension of analysis to more complicated antenna array systems; (iii) other signal processing algorithms that may provide better IR component extraction and scatterer location estimation