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Diagnosis of a brain stroke using wideband microwave scattering

This paper presents a new computer-aided microwave monitoring system as a promising, portable and inexpensive tool to detect and localize brain stroke using a bank of a new wavelet-matched filters. The head is exposed to microwave radiation over the band from 1.1 to 3 GHz, and the backscattered sign...

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Detalles Bibliográficos
Autores principales: Ismail, Dastan, Mustafa, Samah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10031409/
https://www.ncbi.nlm.nih.gov/pubmed/36968233
http://dx.doi.org/10.1098/rsos.221560
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author Ismail, Dastan
Mustafa, Samah
author_facet Ismail, Dastan
Mustafa, Samah
author_sort Ismail, Dastan
collection PubMed
description This paper presents a new computer-aided microwave monitoring system as a promising, portable and inexpensive tool to detect and localize brain stroke using a bank of a new wavelet-matched filters. The head is exposed to microwave radiation over the band from 1.1 to 3 GHz, and the backscattered signals at a hemi-elliptical array of 16 antenna elements surrounding the head are filtered to analyse the perturbation in the microwave signals from the brain. A novel technique is applied to remove the strong reflection from the air–skull interface as a way to estimate the target response and is compared with different techniques from literature to portray their role in the performance. The study results approve that the intensity and the distribution of wavelet energy and Shannon wavelet entropy in the filtered microwave signal, and the novel tool based on the distance between the wavelet energies at symmetric opposite antennas are promising candidate signatures for computer-aided detection and localization of a stroke.
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spelling pubmed-100314092023-03-23 Diagnosis of a brain stroke using wideband microwave scattering Ismail, Dastan Mustafa, Samah R Soc Open Sci Engineering This paper presents a new computer-aided microwave monitoring system as a promising, portable and inexpensive tool to detect and localize brain stroke using a bank of a new wavelet-matched filters. The head is exposed to microwave radiation over the band from 1.1 to 3 GHz, and the backscattered signals at a hemi-elliptical array of 16 antenna elements surrounding the head are filtered to analyse the perturbation in the microwave signals from the brain. A novel technique is applied to remove the strong reflection from the air–skull interface as a way to estimate the target response and is compared with different techniques from literature to portray their role in the performance. The study results approve that the intensity and the distribution of wavelet energy and Shannon wavelet entropy in the filtered microwave signal, and the novel tool based on the distance between the wavelet energies at symmetric opposite antennas are promising candidate signatures for computer-aided detection and localization of a stroke. The Royal Society 2023-03-22 /pmc/articles/PMC10031409/ /pubmed/36968233 http://dx.doi.org/10.1098/rsos.221560 Text en © 2023 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited.
spellingShingle Engineering
Ismail, Dastan
Mustafa, Samah
Diagnosis of a brain stroke using wideband microwave scattering
title Diagnosis of a brain stroke using wideband microwave scattering
title_full Diagnosis of a brain stroke using wideband microwave scattering
title_fullStr Diagnosis of a brain stroke using wideband microwave scattering
title_full_unstemmed Diagnosis of a brain stroke using wideband microwave scattering
title_short Diagnosis of a brain stroke using wideband microwave scattering
title_sort diagnosis of a brain stroke using wideband microwave scattering
topic Engineering
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10031409/
https://www.ncbi.nlm.nih.gov/pubmed/36968233
http://dx.doi.org/10.1098/rsos.221560
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