Microwave tomography with phaseless data on the calcaneus by means of artificial neural networks

Autores
Fajardo, J. E.; Lotto, F. P.; Vericat, F.; Carlevaro, C. M.; Irastorza, R. M.
Año de publicación
2019
Idioma
inglés
Tipo de recurso
artículo
Estado
versión aceptada
Descripción
The aim of this study is to use a Multilayer Perceptron (MLP) Artificial Neural Network (ANN) for phaseless imaging the human heel (modeled as a bilayer dielectric media: bone and surrounding tissue) and the calcaneus cross-section size and location using a two dimensional (2D) microwave tomographic array. Computer simulations were performed over 2D dielectric maps inspired by Computed Tomography (CT) images of human heels for training and testing the MLP. A morphometric analysis was performed to account for the scatterer shape influence on the results. A robustness analysis was also conducted in order to study the MLP performance in noisy conditions. The standard deviations of the relative percentage errors on estimating the dielectric properties of the calcaneus bone were relatively high. Regarding the calcaneus surrounding tissue, the dielectric parameters estimations are better, with relative percentage error standard deviations up to 15%. The location and size of the calcaneus are always properly estimated with absolute error standard deviations up to 3 mm.
Fil: Fajardo, J. E. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física de Líquidos y Sistemas Biológicos; Argentina.
Fil: Lotto, F. P. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física de Líquidos y Sistemas Biológicos; Argentina.
Fil: Vericat, F. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física de Líquidos y Sistemas Biológicos; Argentina.
Fil: Carlevaro, C. M. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física de Líquidos y Sistemas Biológicos; Argentina.
Fil: Carlevaro, C. M. Universidad Tecnológica Nacional. Facultad Regional La Plata. Departamento de Ingeniería Mecánica; Argentina.
Fil: Irastorza, R. M. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física de Líquidos y Sistemas Biológicos; Argentina.
Fil: Irastorza, R. M. Universidad Nacional Arturo Jauretche. Instituto de Ingeniería y Agronomía; Argentina.
Materia
Calcaneus;
Cancellous bone;
Microwave Tomography;
Dielectric properties;
Deep learning;
Artificial Neural Networks;
Nivel de accesibilidad
acceso abierto
Condiciones de uso
info:ar-repo/semantics/accesoabierto
Repositorio
Repositorio Institucional Digital de Acceso Abierto
Institución
Universidad Nacional Arturo Jauretche
OAI Identificador
oai:rid.unaj.edu.ar:123456789/3648
Acceder
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oai_identifier_str oai:rid.unaj.edu.ar:123456789/3648
network_acronym_str RIDUNAJ
repository_id_str
network_name_str Repositorio Institucional Digital de Acceso Abierto
spelling Microwave tomography with phaseless data on the calcaneus by means of artificial neural networksFajardo, J. E.Lotto, F. P.Vericat, F.Carlevaro, C. M.Irastorza, R. M.Calcaneus;Cancellous bone;Microwave Tomography;Dielectric properties;Deep learning;Artificial Neural Networks;The aim of this study is to use a Multilayer Perceptron (MLP) Artificial Neural Network (ANN) for phaseless imaging the human heel (modeled as a bilayer dielectric media: bone and surrounding tissue) and the calcaneus cross-section size and location using a two dimensional (2D) microwave tomographic array. Computer simulations were performed over 2D dielectric maps inspired by Computed Tomography (CT) images of human heels for training and testing the MLP. A morphometric analysis was performed to account for the scatterer shape influence on the results. A robustness analysis was also conducted in order to study the MLP performance in noisy conditions. The standard deviations of the relative percentage errors on estimating the dielectric properties of the calcaneus bone were relatively high. Regarding the calcaneus surrounding tissue, the dielectric parameters estimations are better, with relative percentage error standard deviations up to 15%. The location and size of the calcaneus are always properly estimated with absolute error standard deviations up to 3 mm.Fil: Fajardo, J. E. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física de Líquidos y Sistemas Biológicos; Argentina.Fil: Lotto, F. P. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física de Líquidos y Sistemas Biológicos; Argentina.Fil: Vericat, F. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física de Líquidos y Sistemas Biológicos; Argentina.Fil: Carlevaro, C. M. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física de Líquidos y Sistemas Biológicos; Argentina.Fil: Carlevaro, C. M. Universidad Tecnológica Nacional. Facultad Regional La Plata. Departamento de Ingeniería Mecánica; Argentina.Fil: Irastorza, R. M. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física de Líquidos y Sistemas Biológicos; Argentina.Fil: Irastorza, R. M. Universidad Nacional Arturo Jauretche. Instituto de Ingeniería y Agronomía; Argentina.2019-12-20info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://rid.unaj.edu.ar/handle/123456789/3648engMedical & Biological Engineering & Computing, 58(2)info:eu-repo/semantics/altIdentifier/doi/10.1007/s11517-019-02090-yinfo:eu-repo/semantics/altIdentifier/doi/10.48550/arXiv.1902.07777info:eu-repo/semantics/altIdentifier/eissn/1741-0444info:eu-repo/semantics/altIdentifier/url/doi.org/10.48550/arXiv.1902.07777info:eu-repo/semantics/altIdentifier/url/doi.org/10.1007/s11517-019-02090-yinfo:eu-repo/semantics/openAccessinfo:ar-repo/semantics/accesoabiertohttps://creativecommons.org/licenses/by-nc-nd/4.0/reponame:Repositorio Institucional Digital de Acceso Abiertoinstname:Universidad Nacional Arturo Jauretche2026-09-24T13:53:51Zoai:rid.unaj.edu.ar:123456789/3648instacron:UNAJInstitucionalhttps://rid.unaj.edu.ar/homeUniversidad públicahttps://www.unaj.edu.ar/https://rid.unaj.edu.ar/server/oai/snrdrepositorio@unaj.edu.arArgentinaopendoar:2026-09-24 13:53:51.886Repositorio Institucional Digital de Acceso Abierto - Universidad Nacional Arturo Jauretchefalse
dc.title.none.fl_str_mv Microwave tomography with phaseless data on the calcaneus by means of artificial neural networks
title Microwave tomography with phaseless data on the calcaneus by means of artificial neural networks
spellingShingle Microwave tomography with phaseless data on the calcaneus by means of artificial neural networks
Fajardo, J. E.
Calcaneus;
Cancellous bone;
Microwave Tomography;
Dielectric properties;
Deep learning;
Artificial Neural Networks;
title_short Microwave tomography with phaseless data on the calcaneus by means of artificial neural networks
title_full Microwave tomography with phaseless data on the calcaneus by means of artificial neural networks
title_fullStr Microwave tomography with phaseless data on the calcaneus by means of artificial neural networks
title_full_unstemmed Microwave tomography with phaseless data on the calcaneus by means of artificial neural networks
title_sort Microwave tomography with phaseless data on the calcaneus by means of artificial neural networks
dc.creator.none.fl_str_mv Fajardo, J. E.
Lotto, F. P.
Vericat, F.
Carlevaro, C. M.
Irastorza, R. M.
author Fajardo, J. E.
author_facet Fajardo, J. E.
Lotto, F. P.
Vericat, F.
Carlevaro, C. M.
Irastorza, R. M.
author_role author
author2 Lotto, F. P.
Vericat, F.
Carlevaro, C. M.
Irastorza, R. M.
author2_role author
author
author
author
dc.subject.none.fl_str_mv Calcaneus;
Cancellous bone;
Microwave Tomography;
Dielectric properties;
Deep learning;
Artificial Neural Networks;
topic Calcaneus;
Cancellous bone;
Microwave Tomography;
Dielectric properties;
Deep learning;
Artificial Neural Networks;
dc.description.none.fl_txt_mv The aim of this study is to use a Multilayer Perceptron (MLP) Artificial Neural Network (ANN) for phaseless imaging the human heel (modeled as a bilayer dielectric media: bone and surrounding tissue) and the calcaneus cross-section size and location using a two dimensional (2D) microwave tomographic array. Computer simulations were performed over 2D dielectric maps inspired by Computed Tomography (CT) images of human heels for training and testing the MLP. A morphometric analysis was performed to account for the scatterer shape influence on the results. A robustness analysis was also conducted in order to study the MLP performance in noisy conditions. The standard deviations of the relative percentage errors on estimating the dielectric properties of the calcaneus bone were relatively high. Regarding the calcaneus surrounding tissue, the dielectric parameters estimations are better, with relative percentage error standard deviations up to 15%. The location and size of the calcaneus are always properly estimated with absolute error standard deviations up to 3 mm.
Fil: Fajardo, J. E. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física de Líquidos y Sistemas Biológicos; Argentina.
Fil: Lotto, F. P. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física de Líquidos y Sistemas Biológicos; Argentina.
Fil: Vericat, F. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física de Líquidos y Sistemas Biológicos; Argentina.
Fil: Carlevaro, C. M. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física de Líquidos y Sistemas Biológicos; Argentina.
Fil: Carlevaro, C. M. Universidad Tecnológica Nacional. Facultad Regional La Plata. Departamento de Ingeniería Mecánica; Argentina.
Fil: Irastorza, R. M. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Física de Líquidos y Sistemas Biológicos; Argentina.
Fil: Irastorza, R. M. Universidad Nacional Arturo Jauretche. Instituto de Ingeniería y Agronomía; Argentina.
description The aim of this study is to use a Multilayer Perceptron (MLP) Artificial Neural Network (ANN) for phaseless imaging the human heel (modeled as a bilayer dielectric media: bone and surrounding tissue) and the calcaneus cross-section size and location using a two dimensional (2D) microwave tomographic array. Computer simulations were performed over 2D dielectric maps inspired by Computed Tomography (CT) images of human heels for training and testing the MLP. A morphometric analysis was performed to account for the scatterer shape influence on the results. A robustness analysis was also conducted in order to study the MLP performance in noisy conditions. The standard deviations of the relative percentage errors on estimating the dielectric properties of the calcaneus bone were relatively high. Regarding the calcaneus surrounding tissue, the dielectric parameters estimations are better, with relative percentage error standard deviations up to 15%. The location and size of the calcaneus are always properly estimated with absolute error standard deviations up to 3 mm.
publishDate 2019
dc.date.none.fl_str_mv 2019-12-20
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://rid.unaj.edu.ar/handle/123456789/3648
url https://rid.unaj.edu.ar/handle/123456789/3648
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Medical & Biological Engineering & Computing, 58(2)
info:eu-repo/semantics/altIdentifier/doi/10.1007/s11517-019-02090-y
info:eu-repo/semantics/altIdentifier/doi/10.48550/arXiv.1902.07777
info:eu-repo/semantics/altIdentifier/eissn/1741-0444
info:eu-repo/semantics/altIdentifier/url/doi.org/10.48550/arXiv.1902.07777
info:eu-repo/semantics/altIdentifier/url/doi.org/10.1007/s11517-019-02090-y
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
info:ar-repo/semantics/accesoabierto
https://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv info:ar-repo/semantics/accesoabierto
https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositorio Institucional Digital de Acceso Abierto
instname:Universidad Nacional Arturo Jauretche
reponame_str Repositorio Institucional Digital de Acceso Abierto
collection Repositorio Institucional Digital de Acceso Abierto
instname_str Universidad Nacional Arturo Jauretche
repository.name.fl_str_mv Repositorio Institucional Digital de Acceso Abierto - Universidad Nacional Arturo Jauretche
repository.mail.fl_str_mv repositorio@unaj.edu.ar
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score 12.754232

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