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dc.contributor.authorAzian Azamimi, Abdullah
dc.contributor.authorBu, Sze Chize
dc.contributor.authorNishio, Yoshifumi
dc.date.accessioned2012-10-18T07:47:40Z
dc.date.available2012-10-18T07:47:40Z
dc.date.issued2012-02-27
dc.identifier.citationp. 611-615en_US
dc.identifier.isbn978-145771989-9
dc.identifier.urihttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6178990
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/21399
dc.descriptionLink to publisher's homepage at http://ieeexplore.ieee.org/en_US
dc.description.abstractImage processing plays an important role in medical diagnosis. In this paper, a brain tumor detection method based on cellular neural networks (CNNs) is proposed. Brain tumor is an abnormal growth of cells inside the skull. To examine the location of tumor in the brain, Magnetic Resonance Imaging (MRI) is used. Radiologists will evaluate the grey scale MRI images. This procedure is really time and energy consuming. To overcome this problem, an automated detection method for brain tumor using CNN is developed. By using the template in the CNN simulator, output of the desired image can be performed. Therefore, many templates were combined in order to obtain an accurate result that will help radiologists detecting the tumor in brain images easily.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.ispartofseriesProceedings of the International Conference on Biomedical Engineering (ICoBE 2012)en_US
dc.subjectBrain tumoren_US
dc.subjectMagnetic Resonance Imaging (MRI) imagesen_US
dc.subjectcellular neural networks (CNNs)en_US
dc.subjectTemplatesen_US
dc.subjectImage processingen_US
dc.titleImplementation of an improved cellular neural network algorithm for brain tumor detectionen_US
dc.typeWorking Paperen_US
dc.contributor.urlazamimi@unimap.edu.myen_US
dc.contributor.urlnishio@unimap.edu.myen_US


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