MR Brain Image Classification: A Comparative Study on Machine Learning Methods

Detalhes bibliográficos
Autor(a) principal: Bhowmick, ShibSankar
Data de Publicação: 2014
Outros Autores: Saha, Indrajit, Rato, Luis, Bhattacharjee, Debotosh
Tipo de documento: Artigo
Idioma: por
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10174/17950
Resumo: The brain tissue classification from magnetic resonance images provides valuable insight in neurological research study. A significant number of computational methods have been developed for pixel classification of magnetic resonance brain images. Here, we have shown a comparative study of various machine learning methods for this. The results of the classifiers are evaluated through prediction error analysis and several other performance measures. It is noticed from the results that the Support Vector Machine outperformed other classifiers. The superiority of the results is also established through statistical tests called Friedman test.
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spelling MR Brain Image Classification: A Comparative Study on Machine Learning MethodsMachine LearningStatistical Test.Multi-spectral Magnetic ResonanceImageSupervised ClassifiersThe brain tissue classification from magnetic resonance images provides valuable insight in neurological research study. A significant number of computational methods have been developed for pixel classification of magnetic resonance brain images. Here, we have shown a comparative study of various machine learning methods for this. The results of the classifiers are evaluated through prediction error analysis and several other performance measures. It is noticed from the results that the Support Vector Machine outperformed other classifiers. The superiority of the results is also established through statistical tests called Friedman test.ECT / Universidade de Évora2016-03-11T11:50:16Z2016-03-112014-02-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/17950http://hdl.handle.net/10174/17950porBhowmick, S., Saha I., Rato L., Bhattacharjee D., MR Brain Image Classification: A Comparative Study on Machine Learning Methods, Actas das 4 as Jornadas de Informática da Universidade de Évora, 2014ndndlmr@uevora.ptnd498Bhowmick, ShibSankarSaha, IndrajitRato, LuisBhattacharjee, Debotoshinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-03T19:05:45Zoai:dspace.uevora.pt:10174/17950Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:09:56.425738Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv MR Brain Image Classification: A Comparative Study on Machine Learning Methods
title MR Brain Image Classification: A Comparative Study on Machine Learning Methods
spellingShingle MR Brain Image Classification: A Comparative Study on Machine Learning Methods
Bhowmick, ShibSankar
Machine Learning
Statistical Test.
Multi-spectral Magnetic Resonance
Image
Supervised Classifiers
title_short MR Brain Image Classification: A Comparative Study on Machine Learning Methods
title_full MR Brain Image Classification: A Comparative Study on Machine Learning Methods
title_fullStr MR Brain Image Classification: A Comparative Study on Machine Learning Methods
title_full_unstemmed MR Brain Image Classification: A Comparative Study on Machine Learning Methods
title_sort MR Brain Image Classification: A Comparative Study on Machine Learning Methods
author Bhowmick, ShibSankar
author_facet Bhowmick, ShibSankar
Saha, Indrajit
Rato, Luis
Bhattacharjee, Debotosh
author_role author
author2 Saha, Indrajit
Rato, Luis
Bhattacharjee, Debotosh
author2_role author
author
author
dc.contributor.author.fl_str_mv Bhowmick, ShibSankar
Saha, Indrajit
Rato, Luis
Bhattacharjee, Debotosh
dc.subject.por.fl_str_mv Machine Learning
Statistical Test.
Multi-spectral Magnetic Resonance
Image
Supervised Classifiers
topic Machine Learning
Statistical Test.
Multi-spectral Magnetic Resonance
Image
Supervised Classifiers
description The brain tissue classification from magnetic resonance images provides valuable insight in neurological research study. A significant number of computational methods have been developed for pixel classification of magnetic resonance brain images. Here, we have shown a comparative study of various machine learning methods for this. The results of the classifiers are evaluated through prediction error analysis and several other performance measures. It is noticed from the results that the Support Vector Machine outperformed other classifiers. The superiority of the results is also established through statistical tests called Friedman test.
publishDate 2014
dc.date.none.fl_str_mv 2014-02-01T00:00:00Z
2016-03-11T11:50:16Z
2016-03-11
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10174/17950
http://hdl.handle.net/10174/17950
url http://hdl.handle.net/10174/17950
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv Bhowmick, S., Saha I., Rato L., Bhattacharjee D., MR Brain Image Classification: A Comparative Study on Machine Learning Methods, Actas das 4 as Jornadas de Informática da Universidade de Évora, 2014
nd
nd
lmr@uevora.pt
nd
498
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv ECT / Universidade de Évora
publisher.none.fl_str_mv ECT / Universidade de Évora
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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