Please use this identifier to cite or link to this item: https://olympias.lib.uoi.gr/jspui/handle/123456789/13923
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dc.contributor.authorKarvelis, P. S.en
dc.contributor.authorFotiadis, D. I.en
dc.contributor.authorTsalikakis, D. G.en
dc.contributor.authorGeorgiou, I. A.en
dc.date.accessioned2015-11-24T17:34:03Z-
dc.date.available2015-11-24T17:34:03Z-
dc.identifier.issn1089-7771-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/13923-
dc.rightsDefault Licence-
dc.subjectbayes ruleen
dc.subjectchromosomeen
dc.subjectvector median filter (vmf)en
dc.subjectwatershed transform (wt)en
dc.subjectin-situ hybridizationen
dc.subjectcolor imagesen
dc.subjectdirectional filtersen
dc.subjectm-fishen
dc.subjectidentificationen
dc.subjectsegmentationen
dc.subjectlocalizationen
dc.subjectalgorithmen
dc.subjectnoiseen
dc.titleEnhancement of Multichannel Chromosome Classification Using a Region-Based Classifier and Vector Median Filteringen
heal.typejournalArticle-
heal.type.enJournal articleen
heal.type.elΆρθρο Περιοδικούel
heal.identifier.primaryDoi 10.1109/Titb.2008.2008716-
heal.identifier.secondary<Go to ISI>://000267835800019-
heal.languageen-
heal.accesscampus-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Επιστήμης Υλικώνel
heal.publicationDate2009-
heal.abstractMultichannel chromosome image acquisition is used for cancer diagnosis and research on genetic disorders. This type of imaging, apart from aiding the cytogeneticist in several ways, facilitates the visual detection of chromosome abnormalities. However, chromosome misclassification errors result from different factors, such as uneven hybridization, spectral overlap among fluors, and biochemical noise. In this paper, we enhance the chromosome classification accuracy by making use of a region Bayes classifier that increases the classification accuracy when compared to the already developed pixel-by-pixel classifier and by incorporating the vector median filtering approach for filtering of the image. The method is evaluated using a publicly available database that contains 183 six-channel chromosome sets of images. The overall improvement on the chromosome classification accuracy is 9.99%, compared to the pixel-by-pixel classifier without filtering. This improvement in the chromosome classification accuracy would allow subtle deoxyribonucleic acid abnormalities to be identified easily. The efficiency of the method might further improve by using features extracted from each region and a more sophisticated classifier.en
heal.journalNameIeee Transactions on Information Technology in Biomedicineen
heal.journalTypepeer reviewed-
heal.fullTextAvailabilityTRUE-
Appears in Collections:Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά)

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