Segmentation of complementary dna microarray images using the fuzzy gaussian mixture model technique

dc.contributor.author	Αθανασιάδης, Εμμανουήλ Ι.	el
dc.contributor.author	Κάβουρας, Διονύσης Α.	el
dc.contributor.author	Σπυρίδωνος, Παναγιώτα Π.	el
dc.contributor.author	Γκλώτσος, Δημήτριος	el
dc.contributor.author	Καλατζής, Ιωάννης	el
dc.date.accessioned	2015-05-14T16:20:43Z
dc.date.available	2015-05-14T16:20:43Z
dc.date.issued	2015-05-14
dc.identifier.uri	http://hdl.handle.net/11400/10389
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.130.7897&rep=rep1&type=pdf	en
dc.subject	Segmentation
dc.subject	Microarray image
dc.subject	Κατάτμηση
dc.subject	Εικόνες μικροσυστοιχιών
dc.title	Segmentation of complementary dna microarray images using the fuzzy gaussian mixture model technique	en
heal.type	conferenceItem
heal.generalDescription	Proceedings	en
heal.classification	Technology
heal.classification	Biomedical engineering
heal.classification	Τεχνολογία
heal.classification	Βιοϊατρική τεχνολογία
heal.classificationURI	http://zbw.eu/stw/descriptor/10470-6
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh85014237
heal.classificationURI	N/A-Τεχνολογία
heal.classificationURI	N/A-Βιοϊατρική τεχνολογία
heal.contributorName	Νικηφορίδης, Γεώργιος Χ.	el
heal.language	en
heal.access	free
heal.recordProvider	Τ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Βιοϊατρικής Τεχνολογίας Τ.Ε.	el
heal.publicationDate	2006
heal.bibliographicCitation	Athanasiadis, E., Cavouras, D., Spyridonos, P., Glotsos, D., Kalatzis, I., et al. (2006). Segmentation of complementary dna microarray images using the fuzzy gaussian mixture model technique. Proceedings of the International Special Topic Conference on Information Technology in Biomedicine (ITAB 2006). Ioannina, 26th-28th October 2006. Available from: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.130.7897&rep=rep1&type=pdf	en
heal.abstract	The objective of this work was to investigate the segmentation ability of the Fuzzy Gaussian Mixture Models (FGMM) clustering algorithm, applied on complementary DNA (cDNA) images. A Simulated Microarray image of 200 cells, each containing one spot, was produced following standard established procedure. An automatic gridding process was developed and applied on the microarray image for the task of locating spot borders and surrounding background in each cell. The FGMM and the Gaussian Mixture Model (GMM) algorithms were applied to each cell, with the purpose of discriminating foreground from background. The segmentation abilities of both algorithms were evaluated by means of the segmentation matching factor in respect to the actual classes (foreground-background pixels) of the simulated spots. The FGMM was found to perform better and with equal processing time, as compared to the GMM, rendering the FGMM algorithm an efficient alternative for segmenting cDNA microarray images.	en
heal.fullTextAvailability	true
heal.conferenceName	International Special Topic Conference on Information Technology in Biomedicine	en
heal.conferenceItemType	full paper