A Breast Cancer Detection System Using Metasurfaces With a Convolution Neural Network: A Feasibility Study
Author:
Affiliation:
1. Department of Electrical Engineering, Taif University, Taif, Saudi Arabia
2. Soundskrit Inc., Montreal, QC, Canada
3. Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada
Funder
Taif University
Natural Sciences and Engineering Research Council (NSERC) of Canada
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Condensed Matter Physics,Radiation
Link
http://xplorestaging.ieee.org/ielx7/22/9813473/09772772.pdf?arnumber=9772772
Reference42 articles.
1. 0.5–50 GHz dielectric characterisation of breast cancer tissues
2. The dielectric properties of biological tissues: II. Measurements in the frequency range 10 Hz to 20 GHz
3. Automated Breast Cancer Detection Using Machine Learning Techniques by Extracting Different Feature Extracting Strategies
4. Microwave Radar-Based Differential Breast Cancer Imaging: Imaging in Homogeneous Breast Phantoms and Low Contrast Scenarios
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