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Image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images

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dc.Conferencecode106250
dc.Conferencedate23 December 2013 through 24 December 2013
dc.ConferencelocationKuching, Sarawak
dc.Conferencename2nd International Conference on Advanced Computer Science Applications and Technologies, ACSAT 2013
dc.citedby4
dc.contributor.affiliationsFaculty of Science and Technology
dc.contributor.affiliationsUniversiti Sains Islam Malaysia (USIM)
dc.contributor.affiliationsUniversiti Sains Malaysia (USM)
dc.contributor.authorJabar F.H.A.en_US
dc.contributor.authorIsmail W.en_US
dc.contributor.authorSalam R.A.en_US
dc.contributor.authorHassan R.en_US
dc.date.accessioned2024-05-28T08:25:04Z
dc.date.available2024-05-28T08:25:04Z
dc.date.issued2013
dc.description.abstractClustering is one of the most common automated image segmentation techniques used in many fields including machine learning, pattern recognition, image processing, and bioinformatics. Recently many scientists have performed tremendous research in helping the hematologists in the issue of segmenting the blood cells in the early of prognosis. This paper aims to segment the blood cell images of patients suffering from acute leukemia using an adaptive K-Means clustering together with mean shift algorithm. The integrated clustering techniques have produced comprehensive output images with minimal filtering process to remove the background scene. � 2013 IEEE.
dc.description.natureFinalen_US
dc.identifier.ArtNo6836609
dc.identifier.doi10.1109/ACSAT.2013.80
dc.identifier.epage378
dc.identifier.isbn9781480000000
dc.identifier.scopus2-s2.0-84904205399
dc.identifier.spage373
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84904205399&doi=10.1109%2fACSAT.2013.80&partnerID=40&md5=a87c1dc9ddfd06552747e52822f5bba1
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/8603
dc.languageEnglish
dc.language.isoen_US
dc.publisherIEEE Computer Societyen_US
dc.relation.ispartofProceedings - 2013 International Conference on Advanced Computer Science Applications and Technologies, ACSAT 2013
dc.sourceScopus
dc.subjectacute leukemia cellsen_US
dc.subjectclusteringen_US
dc.subjectimage segmentationen_US
dc.subjectk-meansen_US
dc.subjectmean shiften_US
dc.subjectBlooden_US
dc.subjectCellsen_US
dc.subjectCluster analysisen_US
dc.subjectClustering algorithmsen_US
dc.subjectCytologyen_US
dc.subjectDiagnosisen_US
dc.subjectDiseasesen_US
dc.subjectLearning systemsen_US
dc.subjectPattern recognitionen_US
dc.subjectAcute leukemiaen_US
dc.subjectclusteringen_US
dc.subjectClustering techniquesen_US
dc.subjectK - means clusteringen_US
dc.subjectK-meansen_US
dc.subjectMean shiften_US
dc.titleImage segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images
dc.typeConference Paperen_US
dspace.entity.typePublication

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