McGill Computer Networks Research Lab

Microwave-based techniques for breast tumour detection rely on the inherent electrical difference between malign and healthy tissue in the microwave range. Microwave-radar and microwave-induce thermoacoustic methods both struggle when the dielectric contrast between the tumorous and background tissues is relatively small. In this work, we propose a detection technique that uses a hypothesis testing framework to fuse the information provided by these two sensor modalities and hence provide more reliable detection results in low-contrast, high-clutter environments when compared to the results that either of the techniques would provide alone.