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ANN-based radar approach to detect breast cancers in fibro-glandular tissues: numerical analysis

Published online by Cambridge University Press:  22 August 2017

Salvatore Caorsi  and
Claudio Lenzi Open the ORCID record for Claudio Lenzi [Opens in a new window]
Salvatore Caorsi
Affiliation:
Department of Electrical, Computer and Biomedical Engineering, University of Pavia, via Ferrata 5, 27100 Pavia, Italy
Claudio Lenzi*
Affiliation:
Department of Electrical, Computer and Biomedical Engineering, University of Pavia, via Ferrata 5, 27100 Pavia, Italy
*
Corresponding author: C. Lenzi Email: claudio.lenzi01@ateneopv.it
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Abstract

This paper presents a new artificial neural network (ANN)-based radar data processing approach for the detection of breast cancers located inside fibro-glandular tissues. The aim is not the breast imaging but detecting tumors through ANN processing of data extracted from the radar signals measured around the breast. The proposed approach has been assessed using several realistic two-dimensional breast geometries derived from the models provided by the numerical breast phantom repository of the University of Wisconsin Cross-Disciplinary Electromagnetic Laboratory (UWCEM). The pulsed radar system was assumed to operate in the mono-static configuration. The obtained results showed the abilities of the proposed approach to detect, for any single radar trace, tumors located inside the fibro-glandular tissues with a sensitivity of 93%, a specificity of 90%, and an overall accuracy of 92%.

Keywords

Breast cancer detectionInverse scatteringArtificial neural network
Type
Research Papers
Information
International Journal of Microwave and Wireless Technologies , Volume 9 , Special Issue 8: Biomedical Applications of RF/Microwave and Optics Technologies , October 2017 , pp. 1597 - 1602
Copyright
Copyright © Cambridge University Press and the European Microwave Association 2017 

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