Initial Experimental Tests of an ANN-Based Microwave Imaging Technique for Neck Diagnostics

In this letter, a microwave imaging strategy based on an artificial neural network (ANN) is applied, for the first time, to experimental data gathered from simplified neck phantoms. The ANN is used for solving the underlying inverse scattering problem, with the aim of retrieving the dielectric prope...

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Bibliographic Details
Published inIEEE microwave and wireless components letters Vol. 32; no. 12; pp. 1 - 4
Main Authors Dachena, Chiara, Fedeli, Alessandro, Fanti, Alessandro, Lodi, Matteo B., Fumera, Giorgio, Pastorino, Matteo, Randazzo, Andrea
Format Journal Article
LanguageEnglish
Published IEEE 01.12.2022
Subjects
Artificial neural networks (ANNs)
biomedical imaging
Dielectrics
Imaging
inverse scattering
machine learning (ML)
Microwave imaging
microwave imaging (MWI)
Microwave theory and techniques
Neck
Phantoms
Training
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Summary:In this letter, a microwave imaging strategy based on an artificial neural network (ANN) is applied, for the first time, to experimental data gathered from simplified neck phantoms. The ANN is used for solving the underlying inverse scattering problem, with the aim of retrieving the dielectric properties of the neck for monitoring and diagnostic purposes. The ANN is trained using simulated phantoms, to overcome the limited availability of experimental data. First, a simple configuration with a liquid-filled glass beaker is tested. Then, simplified 3-D-printed models of the human neck are considered. The preliminary findings indicate the possibility of training the network with numerical simulations and testing it against experimental measurements.
ISSN:1531-1309
1558-1764
DOI:10.1109/LMWC.2022.3194805