Research Article
UWB Microwave Imaging for Inclusions Detection: Methodology for Comparing Artefact Removal Algorithms
@INPROCEEDINGS{10.1007/978-3-030-64991-3_4, author={James Puttock and Behnaz Sohani and Banafsheh Khalesi and Gianluigi Tiberi and Sandra Dudley-McEvoy and Mohammad Ghavami}, title={UWB Microwave Imaging for Inclusions Detection: Methodology for Comparing Artefact Removal Algorithms}, proceedings={Body Area Networks. Smart IoT and Big Data for Intelligent Health. 15th EAI International Conference, BODYNETS 2020, Tallinn, Estonia, October 21, 2020, Proceedings}, proceedings_a={BODYNETS}, year={2020}, month={12}, keywords={UWB microwave imaging Image quality metric Artefact removal}, doi={10.1007/978-3-030-64991-3_4} }- James Puttock
Behnaz Sohani
Banafsheh Khalesi
Gianluigi Tiberi
Sandra Dudley-McEvoy
Mohammad Ghavami
Year: 2020
UWB Microwave Imaging for Inclusions Detection: Methodology for Comparing Artefact Removal Algorithms
BODYNETS
Springer
DOI: 10.1007/978-3-030-64991-3_4
Abstract
An investigation is presented on Artefact Removal Methods for Ultra-Wideband (UWB) Microwave Imaging. Simulations have been done representing UWB signals transmitted onto a cylindrical head-mimicking phantom containing an inclusion having dielectric properties imitating an haemorrhagic stroke. The ideal image is constructed by applying a Huygens’ Principle based imaging algorithm to the difference between the electric field outside the cylinder with an inclusion and the electric field outside the same cylinder with no inclusion. Eight different artefact removal methods are then applied, with the inclusion positioned at( \pi )and( - \frac{\pi }{4} )radians, respectively. The ideal image is then used as a reference image to compare the artefact removal methods employing a novel Image Quality Index, calculated using a weighted combination of image quality metrics. The Summed Symmetric Differential method performed very well in our simulations.
