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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/218297
Ver los metadatos del registro completo
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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 Técnicas2025-09-29T10:47:29Zoai: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:34982025-09-29 10:47:30.165CONICET 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 |
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CONICET Digital (CONICET) |
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Consejo Nacional de Investigaciones Científicas y Técnicas |
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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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13.070432 |