Development of a cascade processing method for microarray spot segmentation

dc.contributor.author	Δασκαλάκης, Αντώνης	el
dc.contributor.author	Κάβουρας, Διονύσης Α.	el
dc.contributor.author	Μπουγιούκος, Παναγιώτης	el
dc.contributor.author	Κωστόπουλος, Σπυρίδων	el
dc.contributor.author	Καλατζής, Ιωάννης	el
dc.date.accessioned	2015-05-12T14:16:03Z
dc.date.available	2015-05-12T14:16:03Z
dc.date.issued	2015-05-12
dc.identifier.uri	http://hdl.handle.net/11400/10206
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://link.springer.com/chapter/10.1007/978-3-540-72847-4_53	en
dc.subject	Application
dc.subject	Gene quantification
dc.subject	Εφαρμογή
dc.subject	Ποσοτικοποίηση γονίδίου
dc.title	Development of a cascade processing method for microarray spot segmentation	en
heal.type	conferenceItem
heal.generalDescription	Proccedings	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	Καγκάδης, Γεώργιος Χ.	el
heal.contributorName	Νικηφορίδης, Γεώργιος Σ.	el
heal.identifier.secondary	DOI 10.1007/978-3-540-72847-4_53
heal.language	en
heal.access	campus
heal.recordProvider	Τ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Βιοϊατρικής Τεχνολογίας Τ.Ε.	el
heal.publicationDate	2007
heal.bibliographicCitation	Daskalakis, A., Cavouras, D., Bougioukos, P., Kostopoulos, S., Kalatzis, I., et al. (2007). Development of a cascade processing method for microarray spot segmentation. Proceedings of the 3rd Iberian Conference IbPRIA. Girona, Spain, 6th-8th June 2007. Springer Berlin Heidelberg: 2007. Available from: http://link.springer.com/chapter/10.1007/978-3-540-72847-4_53	en
heal.abstract	A new method is proposed for improving microarray spot segmentation for gene quantification. The method introduces a novel combination of three image processing stages, applied locally to each spot image: i/ Fuzzy C-Means unsupervised clustering, for automatic spot background noise estimation, ii/ power spectrum deconvolution filter design, employing background noise information, for spot image restoration, iii/ Gradient-Vector-Flow (GVF-Snake), for spot boundary delineation. Microarray images used in this study comprised a publicly available dataset obtained from the database of the MicroArray Genome Imaging & Clustering Tool website. The proposed method performed better than the GVF-Snake algorithm (Kullback-Liebler metric: 0.0305 bits against 0.0194 bits) and the SPOT commercial software (pairwise mean absolute error between replicates: 0.234 against 0.303). Application of efficient adaptive spot-image restoration on cDNA microarray images improves spot segmentation and subsequent gene quantification.	de
heal.publisher	Springer Berlin Heidelberg	en
heal.fullTextAvailability	true
heal.conferenceName	Iberian Conference IbPRIA	en
heal.conferenceItemType	full paper