About: Breast cancer detection and classification using support vector machines and pulse coupled neural network

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
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 contrast of 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, we present tests on different breast MRI images. 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 contrast of 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, we present tests on different breast MRI images. (en)
Title	Breast cancer detection and classification using support vector machines and pulse coupled neural network Breast cancer detection and classification using support vector machines and pulse coupled neural network (en)
skos:prefLabel	Breast cancer detection and classification using support vector machines and pulse coupled neural network Breast cancer detection and classification using support vector machines and pulse coupled neural network (en)
skos:notation	RIV/61989100:27240/12:86089246!RIV14-MSM-27240___
http://linked.open...avai/riv/aktivita	S
http://linked.open...avai/riv/aktivity	S
http://linked.open...vai/riv/dodaniDat	2014
http://linked.open...aciTvurceVysledku	Snášel, Václav Kudělka, Miloš
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Vysoká škola báňská - Technická univerzita Ostrava / Fakulta elektrotechniky a informatiky
http://linked.open...dnocenehoVysledku	125498
http://linked.open...ai/riv/idVysledku	RIV/61989100:27240/12:86089246
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Wavelet-based Feature; Type II fuzzy sets; Regions of interest; Region of interest; Pulse coupled neural network; Original images; Input image; Hybrid scheme; Descriptors; Breast MRI; Breast cancer imaging; Breast cancer detection; Breast Cancer (en)
http://linked.open.../riv/klicoveSlovo	Input image Breast Cancer Breast MRI Breast cancer detection Breast cancer imaging Descriptors Hybrid scheme Original images Pulse coupled neural network Region of interest Regions of interest Type II fuzzy sets Wavelet-based Feature
http://linked.open...ontrolniKodProRIV	[6798316451E9]
http://linked.open...v/mistoKonaniAkce	Praha
http://linked.open...i/riv/mistoVydani	Heidelberg
http://linked.open...i/riv/nazevZdroje	Advances in Intelligent Systems and Computing. Volume 179
http://linked.open...in/vavai/riv/obor	IN
http://linked.open...ichTvurcuVysledku	2 (xsd:int)
http://linked.open...cetTvurcuVysledku	4 (xsd:int)
http://linked.open...UplatneniVysledku	2012
http://linked.open...iv/tvurceVysledku	Hassanien, A. E. Snášel, Václav El-Bendary, N. Kudělka, Miloš
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2011-08-29 (xsd:date)
issn	2194-5357
number of pages	11 (xsd:int)
http://bibframe.org/vocab/doi	10.1007/978-3-642-31603-6_23
http://purl.org/ne...btex#hasPublisher	Springer-Verlag
https://schema.org/isbn	978-3-642-31602-9
http://localhost/t...ganizacniJednotka	27240

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