Investigation of classification algorithms for a prototype microwave breast cancer monitor

Author

Santorelli, Adam ; Yunpeng Li ; Porter, Emily ; Popovic, M. ; Coates, Mark

Author_Institution

Dept. of Electr. Eng., McGill Univ., Montreal, QC, Canada

fYear

2014

fDate

6-11 April 2014

Firstpage

320

Lastpage

324

Abstract

In this paper we investigate the use of differential signals to monitor changes within the breast. Specifically, we focus on the use of machine learning classification algorithms to determine whether any malignant tissues are developing. Experimental data is obtained from a 16-element antenna array that transmits a 2-4 GHz broadband pulse. We implement both the Linear Discriminant Analysis and Support Vector Machine (SVM) detection algorithms to analyze the experimentally obtained data.

Keywords

UHF antennas; biological tissues; cancer; learning (artificial intelligence); mammography; medical signal processing; microwave antenna arrays; patient monitoring; signal classification; support vector machines; 16-element antenna array; SVM detection algorithms; broadband pulse; frequency 2 GHz to 4 GHz; linear discriminant analysis; machine learning classification algorithms; malignant tissues; prototype microwave breast cancer monitor; support vector machine; Breast; Feature extraction; Microwave antennas; Phantoms; Support vector machines; Tumors; cancer detection; classification algorithms; microwave sensors;

fLanguage

English

Publisher

ieee

Conference_Titel

Antennas and Propagation (EuCAP), 2014 8th European Conference on

Conference_Location

The Hague

Type

conf

DOI

10.1109/EuCAP.2014.6901757

Filename

6901757