Interferogram-based breast tumor classification using microwave-induced thermoacoustic imaging

Microwave-induced thermoacoustic (TA) imaging combines the dielectric/conductivity contrast in the microwave range with the high resolution of ultrasound imaging. Lack of ionizing radiation exposure in TA imaging makes this technique suitable for frequent screening applications, as with breast cancer screening. In this paper we demonstrate breast tumor classification based on TA imaging. The sensitivity of the signal-based classification algorithm to errors in the estimation of tumor locations is investigated. To reduce this sensitivity, we propose to use the interferogram of received pressure waves as the feature basis used for classification, and demonstrate the robustness based on a finite-difference time-domain (FDTD) simulation framework.