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PIER PIER B PIER C PIER M PIER Letters
2013-12-16
Investigation of Classifiers for Tumor Detection with an Experimental Time-Domain Breast Screening System
By
Adam Santorelli,

    Mr. Adam Santorelli

    Department of Electrical and Computer Engineering

    McGill University

    Canada

    Homepage

Emily Porter,

    Dr. Emily Porter

    Department of Electrical and Computer Engineering

    McGill University

    Canada

    Homepage

Evgeny Kirshin,

    Dr. Evgeny Kirshin

    Department of Electrical and Computer Engineering

    McConnell Building McGill University

    Canada

    Homepage

Yi Jun Liu,

    Dr. Yi Jun Liu

    Department of Electrical and Computer Engineering

    McConnell Building McGill University

    Canada

    Homepage

Milica Popovic

    Dr. Milica Popovic

    Department of Electrical & Computer Engineering

    McGill University

    Canada

    Homepage

Progress In Electromagnetics Research, Vol. 144, 45-57, 2014
doi:10.2528/PIER13110709
Abstract
In this work we examine, for the first time, the use of classification algorithms for early-stage tumor detection with an experimental time-domain microwave breast screening system. The experimental system contains a 16-element antenna array, and testing is done on breast phantoms that mimic breast tissue dielectric properties. We obtain experimental data from multiple breast phantoms with two possible tumor locations. In this work, we investigate a method for detecting the tumors within the breast but without the usual complexity inherent to image-generation methods, and confirm its feasibility on experimental data. The proposed method uses machine learning techniques, namely Support Vector Machines (SVM) and Linear Discriminant Analysis (LDA), to determine whether the current breast being scanned is tumor-free. Our results show that both SVM and LDA methods have promise as algorithms supporting early breast cancer microwave screening.
Citation
Adam Santorelli, Emily Porter, Evgeny Kirshin, Yi Jun Liu, and Milica Popovic, "Investigation of Classifiers for Tumor Detection with an Experimental Time-Domain Breast Screening System," Progress In Electromagnetics Research, Vol. 144, 45-57, 2014.
doi:10.2528/PIER13110709
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