Rough power set tree for feature selection and classification: Case study on MRI brain tumor
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86096560" target="_blank" >RIV/61989100:27240/14:86096560 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-01781-5_24" target="_blank" >http://dx.doi.org/10.1007/978-3-319-01781-5_24</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-01781-5_24" target="_blank" >10.1007/978-3-319-01781-5_24</a>
Alternative languages
Result language
angličtina
Original language name
Rough power set tree for feature selection and classification: Case study on MRI brain tumor
Original language description
This article presents a feature selection and classification system for 2D brain tumors from Magnetic resonance imaging (MRI) images. The proposed feature selection and classification approach consists of four main phases. Firstly, clustering phase thatapplies the K-means clustering algorithm on 2D brain tumors slices. Secondly, feature extraction phase that extracts the optimum feature subset via using the brightness and circularity ratio. Thirdly, reduct generation phase that uses rough set based onpower set tree algorithm to choose the reduct. Finally, classification phase that applies Multilayer Perceptron Neural Network algorithm on the reduct. Experimental results showed that the proposed classification approach achieved a high recognition ratecompared to other classifiers including Naive Bayes, AD-tree and BF-tree. (C) Springer International Publishing Switzerland 2014.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/EE.2.3.20.0073" target="_blank" >EE.2.3.20.0073: Bio-Inspired Methods: research, development and knowledge transfer</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in Intelligent Systems and Computing. Volume 237
ISBN
978-3-319-01780-8
ISSN
2194-5357
e-ISSN
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Number of pages
12
Pages from-to
259-270
Publisher name
Springer
Place of publication
Basel
Event location
Ostrava
Event date
Aug 22, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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