Cost-sensitive ensemble classifiers for microwave breast cancer detection

Microwave breast cancer detection involves analysing the scattered waveforms of microwave signals that are propagated into the breast. We have developed a microwave-radar time-domain system and performed clinical trials using a prototype. This paper presents a classification architecture based on cost-sensitive support vector machines that is designed to process the signals measured by the 16-element multi-static antenna array. We examine the performance of the classifier by applying it to measurements performed on tissue-mimicking breast phantoms.