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Title: MR Brain Image Classification: A Comparative Study on Machine Learning Methods
Authors: Bhowmick, ShibSankar
Saha, Indrajit
Rato, Luis
Bhattacharjee, Debotosh
Editors: Coelho, Francisco
Abreu, Salvador
Barão, Miguel
Keywords: Machine Learning
Statistical Test.
Multi-spectral Magnetic Resonance
Supervised Classifiers
Issue Date: Feb-2014
Publisher: ECT / Universidade de Évora
Citation: 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
Abstract: 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.
Type: article
Appears in Collections:INF - Artigos em Livros de Actas/Proceedings

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