Computer-aided diagnosis of brain tumors using image enhancement and fuzzy logic
A robust medical image processing system depends upon a variety of aspects, including a proper image enhancement, and an optimal segmentation. An algorithm was proposed in this paper to facilitate the implementation of these two steps. First a Magnetic Resonance (MR) image is enhanced via spatial do...
- Autores:
-
Vianney Kinani, Jean Marie
Rosales Silva, Alberto J.
Gallegos Funes, Francisco J.
Arellano, Alfonso
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2014
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/71810
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/71810
http://bdigital.unal.edu.co/36281/
- Palabra clave:
- MRI
Region of interest
Segmentation
Clustering.
MRI
Region of interest
Segmentation
Clustering
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
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Atribución-NoComercial 4.0 InternacionalDerechos reservados - Universidad Nacional de Colombiahttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Vianney Kinani, Jean Marie71f1d547-e4b8-418f-a321-026ba9ab0d20300Rosales Silva, Alberto J.c935ed25-aa18-468c-87e2-cf8754b7d357300Gallegos Funes, Francisco J.7f0a2e94-f752-48d3-8e0c-51eb695c67f6300Arellano, Alfonso7da7b01b-2693-43b2-b26a-5193e42ab5ab3002019-07-03T14:39:22Z2019-07-03T14:39:22Z2014-01-22https://repositorio.unal.edu.co/handle/unal/71810http://bdigital.unal.edu.co/36281/A robust medical image processing system depends upon a variety of aspects, including a proper image enhancement, and an optimal segmentation. An algorithm was proposed in this paper to facilitate the implementation of these two steps. First a Magnetic Resonance (MR) image is enhanced via spatial domain filtering and its contrast is improved, next, the image is segmented using fuzzy C-mean clustering, then the region of interest which might be the tumor or edema, is detected and delineated. The key advantage of this image processing pipeline is the simultaneous use of features computed from the intensity properties of the image in a cascading pattern which makes the computation self-contained. Performance evaluation of the proposed algorithm was carried out on brain images from different MRI’s and the algorithm proved to be successful, comparing it with other dedicated applications.application/pdfspaUniversidad Nacional de Colombia Sede Medellínhttp://revistas.unal.edu.co/index.php/dyna/article/view/36838Universidad Nacional de Colombia Revistas electrónicas UN DynaDynaDYNA; Vol. 81, núm. 183 (2014); 148-157 Dyna; Vol. 81, núm. 183 (2014); 148-157 2346-2183 0012-7353Vianney Kinani, Jean Marie and Rosales Silva, Alberto J. and Gallegos Funes, Francisco J. and Arellano, Alfonso (2014) Computer-aided diagnosis of brain tumors using image enhancement and fuzzy logic. DYNA; Vol. 81, núm. 183 (2014); 148-157 Dyna; Vol. 81, núm. 183 (2014); 148-157 2346-2183 0012-7353 .Computer-aided diagnosis of brain tumors using image enhancement and fuzzy logicArtículo de revistainfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/ARTMRIRegion of interestSegmentationClustering.MRIRegion of interestSegmentationClusteringORIGINAL36838-194760-1-PB.pdfapplication/pdf2029574https://repositorio.unal.edu.co/bitstream/unal/71810/1/36838-194760-1-PB.pdff9b869c07695ca2b24eace47128865a3MD51THUMBNAIL36838-194760-1-PB.pdf.jpg36838-194760-1-PB.pdf.jpgGenerated Thumbnailimage/jpeg9399https://repositorio.unal.edu.co/bitstream/unal/71810/2/36838-194760-1-PB.pdf.jpgf9f3ff78c8df8cd6682e4ff400b20ed3MD52unal/71810oai:repositorio.unal.edu.co:unal/718102023-06-20 23:03:15.003Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.co |
dc.title.spa.fl_str_mv |
Computer-aided diagnosis of brain tumors using image enhancement and fuzzy logic |
title |
Computer-aided diagnosis of brain tumors using image enhancement and fuzzy logic |
spellingShingle |
Computer-aided diagnosis of brain tumors using image enhancement and fuzzy logic MRI Region of interest Segmentation Clustering. MRI Region of interest Segmentation Clustering |
title_short |
Computer-aided diagnosis of brain tumors using image enhancement and fuzzy logic |
title_full |
Computer-aided diagnosis of brain tumors using image enhancement and fuzzy logic |
title_fullStr |
Computer-aided diagnosis of brain tumors using image enhancement and fuzzy logic |
title_full_unstemmed |
Computer-aided diagnosis of brain tumors using image enhancement and fuzzy logic |
title_sort |
Computer-aided diagnosis of brain tumors using image enhancement and fuzzy logic |
dc.creator.fl_str_mv |
Vianney Kinani, Jean Marie Rosales Silva, Alberto J. Gallegos Funes, Francisco J. Arellano, Alfonso |
dc.contributor.author.spa.fl_str_mv |
Vianney Kinani, Jean Marie Rosales Silva, Alberto J. Gallegos Funes, Francisco J. Arellano, Alfonso |
dc.subject.proposal.spa.fl_str_mv |
MRI Region of interest Segmentation Clustering. MRI Region of interest Segmentation Clustering |
topic |
MRI Region of interest Segmentation Clustering. MRI Region of interest Segmentation Clustering |
description |
A robust medical image processing system depends upon a variety of aspects, including a proper image enhancement, and an optimal segmentation. An algorithm was proposed in this paper to facilitate the implementation of these two steps. First a Magnetic Resonance (MR) image is enhanced via spatial domain filtering and its contrast is improved, next, the image is segmented using fuzzy C-mean clustering, then the region of interest which might be the tumor or edema, is detected and delineated. The key advantage of this image processing pipeline is the simultaneous use of features computed from the intensity properties of the image in a cascading pattern which makes the computation self-contained. Performance evaluation of the proposed algorithm was carried out on brain images from different MRI’s and the algorithm proved to be successful, comparing it with other dedicated applications. |
publishDate |
2014 |
dc.date.issued.spa.fl_str_mv |
2014-01-22 |
dc.date.accessioned.spa.fl_str_mv |
2019-07-03T14:39:22Z |
dc.date.available.spa.fl_str_mv |
2019-07-03T14:39:22Z |
dc.type.spa.fl_str_mv |
Artículo de revista |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.coar.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
dc.type.coarversion.spa.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.content.spa.fl_str_mv |
Text |
dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/ART |
format |
http://purl.org/coar/resource_type/c_6501 |
status_str |
publishedVersion |
dc.identifier.uri.none.fl_str_mv |
https://repositorio.unal.edu.co/handle/unal/71810 |
dc.identifier.eprints.spa.fl_str_mv |
http://bdigital.unal.edu.co/36281/ |
url |
https://repositorio.unal.edu.co/handle/unal/71810 http://bdigital.unal.edu.co/36281/ |
dc.language.iso.spa.fl_str_mv |
spa |
language |
spa |
dc.relation.spa.fl_str_mv |
http://revistas.unal.edu.co/index.php/dyna/article/view/36838 |
dc.relation.ispartof.spa.fl_str_mv |
Universidad Nacional de Colombia Revistas electrónicas UN Dyna Dyna |
dc.relation.ispartofseries.none.fl_str_mv |
DYNA; Vol. 81, núm. 183 (2014); 148-157 Dyna; Vol. 81, núm. 183 (2014); 148-157 2346-2183 0012-7353 |
dc.relation.references.spa.fl_str_mv |
Vianney Kinani, Jean Marie and Rosales Silva, Alberto J. and Gallegos Funes, Francisco J. and Arellano, Alfonso (2014) Computer-aided diagnosis of brain tumors using image enhancement and fuzzy logic. DYNA; Vol. 81, núm. 183 (2014); 148-157 Dyna; Vol. 81, núm. 183 (2014); 148-157 2346-2183 0012-7353 . |
dc.rights.spa.fl_str_mv |
Derechos reservados - Universidad Nacional de Colombia |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.license.spa.fl_str_mv |
Atribución-NoComercial 4.0 Internacional |
dc.rights.uri.spa.fl_str_mv |
http://creativecommons.org/licenses/by-nc/4.0/ |
dc.rights.accessrights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Atribución-NoComercial 4.0 Internacional Derechos reservados - Universidad Nacional de Colombia http://creativecommons.org/licenses/by-nc/4.0/ http://purl.org/coar/access_right/c_abf2 |
eu_rights_str_mv |
openAccess |
dc.format.mimetype.spa.fl_str_mv |
application/pdf |
dc.publisher.spa.fl_str_mv |
Universidad Nacional de Colombia Sede Medellín |
institution |
Universidad Nacional de Colombia |
bitstream.url.fl_str_mv |
https://repositorio.unal.edu.co/bitstream/unal/71810/1/36838-194760-1-PB.pdf https://repositorio.unal.edu.co/bitstream/unal/71810/2/36838-194760-1-PB.pdf.jpg |
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