SVM-Based Microwave Breast Tumour Classification

Ang Chen; Yuzhuo Gu; Songchun Zhang

doi:10.1109/ICPHDS53608.2021.00042

2021 International Conference on Public Health and Data Science (ICPHDS)

SVM-Based Microwave Breast Tumour Classification

Year: 2021, Pages: 174-177

DOI Bookmark: 10.1109/ICPHDS53608.2021.00042

Authors

Ang Chen, Hohai University,College of Internet of Things Engineering,Changzhou,China
Yuzhuo Gu, Northeastern University,College of Medicine and Biological Information Engineering,Shenyang,China
Songchun Zhang, Hunan University,School of Electrical and Information Engineering,Changsha,China

Abstract

This paper presents the feasibility of the benign and malignant breast tumor classification according to dielectric properties. The experiment data are obtained by simulating the human breast with the help of COMSOL Multiphysics, in which way electric field amplitude of different samples is collected. Support Vector Machines (SVM) is utilized to analyze the microwave signal and distinguish benign and malignant breast tumors. The capability and reliability of classification are compared with Decision Tree and Random Forest.

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SVM-Based Microwave Breast Tumour Classification

Authors

Abstract

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