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Brain tumor segmentation and classification using KNN algorithm

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dc.citedby7
dc.contributor.authorSuhartonoen_US
dc.contributor.authorNguyen P.T.en_US
dc.contributor.authorShankar K.en_US
dc.contributor.authorHashim W.en_US
dc.contributor.authorMaseleno A.en_US
dc.contributor.authorid57210948011en_US
dc.contributor.authorid57216386109en_US
dc.contributor.authorid56884031900en_US
dc.contributor.authorid11440260100en_US
dc.contributor.authorid55354910900en_US
dc.date.accessioned2023-05-29T07:24:18Z
dc.date.available2023-05-29T07:24:18Z
dc.date.issued2019
dc.description.abstractImage processing plays a vital role in MRI image processing. MRI images are widely used in medical fields for analysis and detection of tumour growth from the body. There are varieties of efficient brain tumour detection and segmentation methods have been suggested by various researchers for efficient tumour detection. Existing methods encounter with several challenges such as detection time, accuracy and quality of tumour. In this review paper, we are presenting a study of various tumour detection methods for MRI images. A comparative analysis has been also performed for various methods.SAR images are the high resolution images which cannot be collected manually. In this work, we identified the SAR images randomly from web with different region inclusions. The regions in an image include water area, land area and the mountain area. The implementation of proposed model is done in MATLAB environment. � BEIESP.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.35940/ijeat.F1137.0886S19
dc.identifier.epage711
dc.identifier.issue6 Special Issue
dc.identifier.scopus2-s2.0-85071991938
dc.identifier.spage706
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85071991938&doi=10.35940%2fijeat.F1137.0886S19&partnerID=40&md5=0ebe337cd92e3cb84d6e3e74821356c6
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24535
dc.identifier.volume8
dc.publisherBlue Eyes Intelligence Engineering and Sciences Publicationen_US
dc.relation.ispartofAll Open Access, Bronze
dc.sourceScopus
dc.sourcetitleInternational Journal of Engineering and Advanced Technology
dc.titleBrain tumor segmentation and classification using KNN algorithmen_US
dc.typeArticleen_US
dspace.entity.typePublication
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