Segmentation of microarray images using gradient vector flow active contours boosted by gaussian mixture models

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	2015-05-14T17:11:40Z
dc.date.available	2015-05-14T17:11:40Z
dc.date.issued	2015-05-14
dc.identifier.uri	http://hdl.handle.net/11400/10403
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://www.bme.teiath.gr/medisp/pdfs/ATHANASSIADIS_2007_EpsMso_Segmentation%20of%20microarray.pdf	en
dc.subject	Microarrays
dc.subject	Active Contours
dc.subject	Μικροσυστοιχίες
dc.subject	Ενεργά περιγράμματα
dc.title	Segmentation of microarray images using gradient vector flow active contours boosted by gaussian mixture models	en
heal.type	conferenceItem
heal.classification	Medicine
heal.classification	Biomedical engineering
heal.classification	Ιατρική
heal.classification	Βιοϊατρική τεχνολογία
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh00006614
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh85014237
heal.classificationURI	N/A-Ιατρική
heal.classificationURI	N/A-Βιοϊατρική τεχνολογία
heal.contributorName	Νικηφορίδης, Γεώργιος Σ.	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	2007
heal.bibliographicCitation	Athanasiadis, E., Cavouras, D., Spyridonos, P., Glotsos, D., Kalatzis, I., et al. (2007). Segmentation of microarray images using gradient vector flow active contours boosted by gaussian mixture models. In the 2nd International Conference on Experiments/ Process/ System Modelling/ Simulation/ Optimization (2nd IC-EpsMsO). Athens, Greece, 4th – 7th July 2007. Available from: http://www.bme.teiath.gr/medisp/pdfs/ATHANASSIADIS_2007_EpsMso_Segmentation%20of%20microarray.pdf	en
heal.abstract	In this paper, a new methodology for the segmentation of cDNA microarray images is proposed, based on the combination of Gaussian Mixture Models (GMM) with Gradient Vector Flow (GVF) active contours. A simulated microarray image of 1000 spots was produced using a standard procedure. 5 real microarray images were used to evaluate the performance of our algorithm. GMM was firstly applied in all individual cells (spot with each background). The output was used to initialize a GVF active contour. The major advance of our method is that it overcomes limitations of both GMM and active contours when used individually. Segmentation matching factors and mean intensity values were calculated for every cell using GMM, GVF, and the combination of GMM and GVF in the simulated data. Pairwise correlations and mean absolute errors were also calculated by using real microarrays. Numerical experiments using both simulated and real images showed that our method was more accurate in measuring intensity values and detecting actual boundaries of spots, compared with GMM and active contours used individually. Results concerning the segmentability and the mean intensity value of the proposed algorithm were more accurate, as compared with those methods when used individually.	en
heal.fullTextAvailability	true
heal.conferenceName	International Conference on Experiments/ Process/ System Modelling/ Simulation/ Optimization	en
heal.conferenceItemType	poster