Tissue discrimination in magnetic resonance imaging of the rotator cuff

Autores
Meschino, Gustavo Javier; Comas, Diego Sebastián; Gonzalez, Mariela Azul; Capiel, Carlos Alfredo; Ballarin, Virginia Laura
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Evaluation and diagnosis of diseases of the muscles within the rotator cuff can be done using different modalities, being the Magnetic Resonance the method more widely used. There are criteria to evaluate the degree of fat infiltration and muscle atrophy, but these have low accuracy and show great variability inter and intra observer. In this paper, an analysis of the texture features of the rotator cuff muscles is performed to classify them and other tissues. A general supervised classification approach was used, combining forward-search as feature selection method with kNN as classification rule. Sections of Magnetic Resonance Images of the tissues of interest were selected by specialist doctors and they were considered as Gold Standard. Accuracies obtained were of 93% for T1-weighted images and 92% for T2-weighted images. As an immediate future work, the combination of both sequences of images will be considered, expecting to improve the results, as well as the use of other sequences of Magnetic Resonance Images. This work represents an initial point for the classification and quantification of fat infiltration and muscle atrophy degree. From this initial point, it is expected to make an accurate and objective system which will result in benefits for future research and for patients' health.
Fil: Meschino, Gustavo Javier. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Departamento de Ingeniería Eléctrica. Laboratorio de Bioingeniería; Argentina. Universidad FASTA "Santo Tomas de Aquino"; Argentina
Fil: Comas, Diego Sebastián. Universidad Nacional de Mar del Plata. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata; Argentina
Fil: Gonzalez, Mariela Azul. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Departamento de Ingeniería Eléctrica. Laboratorio de Bioingeniería; Argentina. Universidad FASTA "Santo Tomas de Aquino"; Argentina
Fil: Capiel, Carlos Alfredo. Universidad FASTA "Santo Tomas de Aquino"; Argentina
Fil: Ballarin, Virginia Laura. Universidad Nacional de Mar del Plata. Facultad de Ingeniería; Argentina. Universidad FASTA "Santo Tomas de Aquino"; Argentina
Materia
magnetic resonance
rotator cuff
texture
muscle
fat
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/218297
Acceder
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spelling Tissue discrimination in magnetic resonance imaging of the rotator cuffMeschino, Gustavo JavierComas, Diego SebastiánGonzalez, Mariela AzulCapiel, Carlos AlfredoBallarin, Virginia Lauramagnetic resonancerotator cufftexturemusclefathttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2Evaluation and diagnosis of diseases of the muscles within the rotator cuff can be done using different modalities, being the Magnetic Resonance the method more widely used. There are criteria to evaluate the degree of fat infiltration and muscle atrophy, but these have low accuracy and show great variability inter and intra observer. In this paper, an analysis of the texture features of the rotator cuff muscles is performed to classify them and other tissues. A general supervised classification approach was used, combining forward-search as feature selection method with kNN as classification rule. Sections of Magnetic Resonance Images of the tissues of interest were selected by specialist doctors and they were considered as Gold Standard. Accuracies obtained were of 93% for T1-weighted images and 92% for T2-weighted images. As an immediate future work, the combination of both sequences of images will be considered, expecting to improve the results, as well as the use of other sequences of Magnetic Resonance Images. This work represents an initial point for the classification and quantification of fat infiltration and muscle atrophy degree. From this initial point, it is expected to make an accurate and objective system which will result in benefits for future research and for patients' health.Fil: Meschino, Gustavo Javier. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Departamento de Ingeniería Eléctrica. Laboratorio de Bioingeniería; Argentina. Universidad FASTA "Santo Tomas de Aquino"; ArgentinaFil: Comas, Diego Sebastián. Universidad Nacional de Mar del Plata. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata; ArgentinaFil: Gonzalez, Mariela Azul. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Departamento de Ingeniería Eléctrica. Laboratorio de Bioingeniería; Argentina. Universidad FASTA "Santo Tomas de Aquino"; ArgentinaFil: Capiel, Carlos Alfredo. Universidad FASTA "Santo Tomas de Aquino"; ArgentinaFil: Ballarin, Virginia Laura. Universidad Nacional de Mar del Plata. Facultad de Ingeniería; Argentina. Universidad FASTA "Santo Tomas de Aquino"; ArgentinaIOP Publishing2016-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/218297Meschino, Gustavo Javier; Comas, Diego Sebastián; Gonzalez, Mariela Azul; Capiel, Carlos Alfredo; Ballarin, Virginia Laura; Tissue discrimination in magnetic resonance imaging of the rotator cuff; IOP Publishing; Journal of Physics: Conference Series; 705; 1; 5-2016; 1-101742-6596CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://iopscience.iop.org/article/10.1088/1742-6596/705/1/012022/pdfinfo:eu-repo/semantics/altIdentifier/doi/10.1088/1742-6596/705/1/012022info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T12:20:56Zoai:ri.conicet.gov.ar:11336/218297instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-22 12:20:56.649CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Tissue discrimination in magnetic resonance imaging of the rotator cuff
title Tissue discrimination in magnetic resonance imaging of the rotator cuff
spellingShingle Tissue discrimination in magnetic resonance imaging of the rotator cuff
Meschino, Gustavo Javier
magnetic resonance
rotator cuff
texture
muscle
fat
title_short Tissue discrimination in magnetic resonance imaging of the rotator cuff
title_full Tissue discrimination in magnetic resonance imaging of the rotator cuff
title_fullStr Tissue discrimination in magnetic resonance imaging of the rotator cuff
title_full_unstemmed Tissue discrimination in magnetic resonance imaging of the rotator cuff
title_sort Tissue discrimination in magnetic resonance imaging of the rotator cuff
dc.creator.none.fl_str_mv Meschino, Gustavo Javier
Comas, Diego Sebastián
Gonzalez, Mariela Azul
Capiel, Carlos Alfredo
Ballarin, Virginia Laura
author Meschino, Gustavo Javier
author_facet Meschino, Gustavo Javier
Comas, Diego Sebastián
Gonzalez, Mariela Azul
Capiel, Carlos Alfredo
Ballarin, Virginia Laura
author_role author
author2 Comas, Diego Sebastián
Gonzalez, Mariela Azul
Capiel, Carlos Alfredo
Ballarin, Virginia Laura
author2_role author
author
author
author
dc.subject.none.fl_str_mv magnetic resonance
rotator cuff
texture
muscle
fat
topic magnetic resonance
rotator cuff
texture
muscle
fat
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Evaluation and diagnosis of diseases of the muscles within the rotator cuff can be done using different modalities, being the Magnetic Resonance the method more widely used. There are criteria to evaluate the degree of fat infiltration and muscle atrophy, but these have low accuracy and show great variability inter and intra observer. In this paper, an analysis of the texture features of the rotator cuff muscles is performed to classify them and other tissues. A general supervised classification approach was used, combining forward-search as feature selection method with kNN as classification rule. Sections of Magnetic Resonance Images of the tissues of interest were selected by specialist doctors and they were considered as Gold Standard. Accuracies obtained were of 93% for T1-weighted images and 92% for T2-weighted images. As an immediate future work, the combination of both sequences of images will be considered, expecting to improve the results, as well as the use of other sequences of Magnetic Resonance Images. This work represents an initial point for the classification and quantification of fat infiltration and muscle atrophy degree. From this initial point, it is expected to make an accurate and objective system which will result in benefits for future research and for patients' health.
Fil: Meschino, Gustavo Javier. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Departamento de Ingeniería Eléctrica. Laboratorio de Bioingeniería; Argentina. Universidad FASTA "Santo Tomas de Aquino"; Argentina
Fil: Comas, Diego Sebastián. Universidad Nacional de Mar del Plata. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata; Argentina
Fil: Gonzalez, Mariela Azul. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Departamento de Ingeniería Eléctrica. Laboratorio de Bioingeniería; Argentina. Universidad FASTA "Santo Tomas de Aquino"; Argentina
Fil: Capiel, Carlos Alfredo. Universidad FASTA "Santo Tomas de Aquino"; Argentina
Fil: Ballarin, Virginia Laura. Universidad Nacional de Mar del Plata. Facultad de Ingeniería; Argentina. Universidad FASTA "Santo Tomas de Aquino"; Argentina
description Evaluation and diagnosis of diseases of the muscles within the rotator cuff can be done using different modalities, being the Magnetic Resonance the method more widely used. There are criteria to evaluate the degree of fat infiltration and muscle atrophy, but these have low accuracy and show great variability inter and intra observer. In this paper, an analysis of the texture features of the rotator cuff muscles is performed to classify them and other tissues. A general supervised classification approach was used, combining forward-search as feature selection method with kNN as classification rule. Sections of Magnetic Resonance Images of the tissues of interest were selected by specialist doctors and they were considered as Gold Standard. Accuracies obtained were of 93% for T1-weighted images and 92% for T2-weighted images. As an immediate future work, the combination of both sequences of images will be considered, expecting to improve the results, as well as the use of other sequences of Magnetic Resonance Images. This work represents an initial point for the classification and quantification of fat infiltration and muscle atrophy degree. From this initial point, it is expected to make an accurate and objective system which will result in benefits for future research and for patients' health.
publishDate 2016
dc.date.none.fl_str_mv 2016-05
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/218297
Meschino, Gustavo Javier; Comas, Diego Sebastián; Gonzalez, Mariela Azul; Capiel, Carlos Alfredo; Ballarin, Virginia Laura; Tissue discrimination in magnetic resonance imaging of the rotator cuff; IOP Publishing; Journal of Physics: Conference Series; 705; 1; 5-2016; 1-10
1742-6596
CONICET Digital
CONICET
url http://hdl.handle.net/11336/218297
identifier_str_mv Meschino, Gustavo Javier; Comas, Diego Sebastián; Gonzalez, Mariela Azul; Capiel, Carlos Alfredo; Ballarin, Virginia Laura; Tissue discrimination in magnetic resonance imaging of the rotator cuff; IOP Publishing; Journal of Physics: Conference Series; 705; 1; 5-2016; 1-10
1742-6596
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://iopscience.iop.org/article/10.1088/1742-6596/705/1/012022/pdf
info:eu-repo/semantics/altIdentifier/doi/10.1088/1742-6596/705/1/012022
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv IOP Publishing
publisher.none.fl_str_mv IOP Publishing
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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