volume | PIER Journals

Abstract

Breast cancer detection using Ultra Wideband Radar has been thoroughly investigated over the last decade. This breast imaging modality is based on the dielectric properties of normal and cancerous breast tissue at microwave frequencies. However, the dielectric properties of benign and malignant tumours are very similar, so tumour classification based on dielectric properties alone is not feasible. Therefore, classification methods based on the Radar Target Signature of tumours need to be further developed to classify tumours as either benign or malignant. Several studies have addressed the issue of tumour classification based on the size, shape and surface texture of the tumour. In general, these studies examined the performance of classification algorithms in primarily dielectrically homogeneous breast models. These relatively simplistic models do not provide a realistic test platform for the evaluation of tumour classification algorithms. This paper examines the classification of tumours under realistic dielectrically heterogeneous conditions. Four different heterogeneous scenarios are considered, with varying levels of heterogeneity and complexity. In this paper, the performance and robustness of tumour classification algorithms under these realistic conditions are examined and discussed.

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Dr. Raquel Cruz Conceicao

Dr. Martin O'Halloran

Dr. Martin Glavin

Dr. Edward Jones