Please use this identifier to cite or link to this item: https://olympias.lib.uoi.gr/jspui/handle/123456789/13914
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dc.contributor.authorKarvelis, P. S.en
dc.contributor.authorTzallas, A. T.en
dc.contributor.authorFotiadis, D. I.en
dc.contributor.authorGeorgiou, I.en
dc.date.accessioned2015-11-24T17:33:58Z-
dc.date.available2015-11-24T17:33:58Z-
dc.identifier.issn0278-0062-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/13914-
dc.rightsDefault Licence-
dc.subjectbayes classificationen
dc.subjectchromosome imagesen
dc.subjectkaryotypingen
dc.subjectmultichannel segmentationen
dc.subjectmultiplex fluorescent in situ hybridization (m-fish)en
dc.subjectwatershed transformen
dc.subjectin-situ hybridizationen
dc.subjectm-fishen
dc.subjectjoint segmentationen
dc.subjectimagesen
dc.subjectalgorithmen
dc.subjectbinarizationen
dc.subjectgradienten
dc.titleA multichannel watershed-based segmentation method for multispectral chromosome classificationen
heal.typejournalArticle-
heal.type.enJournal articleen
heal.type.elΆρθρο Περιοδικούel
heal.identifier.primaryDoi 10.1109/Tmi.2008.916962-
heal.identifier.secondary<Go to ISI>://000255433500011-
heal.languageen-
heal.accesscampus-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Επιστήμης Υλικώνel
heal.publicationDate2008-
heal.abstractMultiplex fluorescent in situ hybridization (M-FISH) is a recently developed chromosome imaging technique where each chromosome class appears to have a distinct color. This technique not only facilitates the detection of subtle chromosomal aberrations but also makes the analysis of chromosome images easier; both for human inspection and computerized analysis. In this paper, a novel method for segmentation and classification of M-FISH chromosome images is presented. The segmentation is based on the multichannel watershed transform in order to define regions of similar spatial and spectral characteristics. Then, a Bayes classifier, task-specific on region classification, is applied. Our method consists of four basic steps: 1) computation of the gradient magnitude of the image, 2) application of the watershed transform to decompose the image into a set of homogenous regions, 3) classification of each region, and 4) merging of similar adjacent regions. The method is evaluated using a publicly available chromosome image database and the obtained overall accuracy is 82.4%. By introducing the classification of each watershed region, the proposed method achieves substantially better results compared to other methods at a lower computational cost. The combination of the multichannel segmentation and the region-based classification is found to improve the overall classification accuracy compared to pixel-by-pixel approaches.en
heal.journalNameIEEE Trans Med Imagingen
heal.journalTypepeer reviewed-
heal.fullTextAvailabilityTRUE-
Appears in Collections:Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά)

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