Breast cancer detection and classification using support vector machines and pulse coupled neural network
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F12%3A86089246" target="_blank" >RIV/61989100:27240/12:86089246 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-642-31603-6_23" target="_blank" >http://dx.doi.org/10.1007/978-3-642-31603-6_23</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-642-31603-6_23" target="_blank" >10.1007/978-3-642-31603-6_23</a>
Alternative languages
Result language
angličtina
Original language name
Breast cancer detection and classification using support vector machines and pulse coupled neural network
Original language description
This article introduces a hybrid scheme that combines the advantages of pulse coupled neural networks (PCNNs) and support vector machine, in conjunction with type-II fuzzy sets and wavelet to enhance the contrast of the original images and feature extraction. An application of MRI breast cancer imaging has been chosen and hybridization scheme have been applied to see their ability and accuracy to classify the breast cancer images into two outcomes: cancer or non-cancer. In order to enhance the contrastof the input image, identify the region of interest and detect the boundary of the breast pattern, a type-II fuzzy-based enhancement and PCNN-based segmentation were applied. Finally, wavelet-based features are extracted and normalized and a support vector machine classifier were employed to evaluate the ability of the lesion descriptors for discrimination of different regions of interest to determine whether they represent cancer or not. To evaluate the performance of presented approach
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
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2012
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 179
ISBN
978-3-642-31602-9
ISSN
2194-5357
e-ISSN
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Number of pages
11
Pages from-to
269-279
Publisher name
Springer
Place of publication
Heidelberg
Event location
Praha
Event date
Aug 29, 2011
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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