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...

Full description

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
id UNACIONAL2_865338ee969d47e855b2732c446ea8a8
oai_identifier_str oai:repositorio.unal.edu.co:unal/71810
network_acronym_str UNACIONAL2
network_name_str Universidad Nacional de Colombia
repository_id_str
spelling 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
bitstream.checksum.fl_str_mv f9b869c07695ca2b24eace47128865a3
f9f3ff78c8df8cd6682e4ff400b20ed3
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
repository.name.fl_str_mv Repositorio Institucional Universidad Nacional de Colombia
repository.mail.fl_str_mv repositorio_nal@unal.edu.co
_version_ 1814089329023123456