Near-field Sensors with Machine Learning for Breast Tumor Detection

  • Maged A. Aldhaeebi
  • Thamer S. Almoneef
  • Omar M. Ramahi

Abstract

In this work, we propose the use of an electrically small novel antenna as a probe combined with a classification algorithm for near
field microwave breast tumor detection. The resonant probe is
highly sensitive to the changes in the electromagnetic properties of the breast tissues such that the presence of the tumor is estimated
by determining the changes in the magnitude and phase response
of the reflection coefficient of the sensor. The Principle Component placed at the middle of the probe as shown in Fig. 1. The main
Analysis (PCA) feature extraction method is applied to emphasize 
the difference in the probe responses for both the healthy and the
tumourous cases . We show that when a numerical realistic breast 
with and without tumor cells is placed in the near field of the probe, 
the probe is capable of distinguishing between healthy and tumorous tissue. In addition, the probe is able to identify tumors with 
various sizes placed in single locations.

Published
2018-12-24
How to Cite
Aldhaeebi, M., Almoneef, T., & Ramahi, O. (2018). Near-field Sensors with Machine Learning for Breast Tumor Detection. Journal of Computational Vision and Imaging Systems, 4(1), 3. https://doi.org/10.15353/jcvis.v4i1.328