McGill Computer Networks Research Lab

Microwave radar imaging for breast cancer detection is one promising technique to replace/supplement X-ray mammography and MRI. Previously developed imaging algorithms have been applied to the signals generated from breast models comprising large dielectric contrast and relatively homogeneous tissue. This study investigates five imaging algorithms applied to the signals generated from more realistic models. The signals were generated from the finite-difference time-domain simulations of the microwave interaction with breast models. We find that, under a good estimate of the average dielectric properties of the tissue and tumour, the generalized likelihood ratio test algorithm is capable of detecting tumours, in the sense of a good signal-to-interference-and-noise ratio in the presence of reduced dielectric contrast and increased tissue heterogeneity. This establishes the motivation to estimate the average tissue
properties and extend the algorithm to handle multi-static signals for microwave breast imaging.