A comparative study of individual and ensemble majority vote cDNA microarray image segmentation schemes, originating from a spot-adjustable based restoration framework

dc.contributor.author	Δασκαλάκης, Αντώνης	el
dc.contributor.author	Γκλώτσος, Δημήτριος	el
dc.contributor.author	Κωστόπουλος, Σπυρίδων	el
dc.contributor.author	Κάβουρας, Διονύσης Α.	el
dc.contributor.author	Νικηφορίδης, Γεώργιος Σ.	el
dc.date.accessioned	2015-05-14T11:44:20Z
dc.date.available	2015-05-14T11:44:20Z
dc.date.issued	2015-05-14
dc.identifier.uri	http://hdl.handle.net/11400/10362
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.cmpbjournal.com/article/S0169-2607(09)00039-X/abstract	en
dc.source	http://www.sciencedirect.com/science/article/pii/S016926070900039X	en
dc.subject	Segmentation
dc.subject	Restoration
dc.subject	Κατάτμηση
dc.subject	Αποκατάσταση
dc.title	A comparative study of individual and ensemble majority vote cDNA microarray image segmentation schemes, originating from a spot-adjustable based restoration framework	en
heal.type	journalArticle
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.identifier.secondary	DOI: http://dx.doi.org/10.1016/j.cmpb.2009.01.007
heal.language	en
heal.access	campus
heal.recordProvider	Τ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Βιοϊατρικής Τεχνολογίας Τ.Ε.	el
heal.publicationDate	2009
heal.bibliographicCitation	Daskalakis, A., Glotsos, D., Kostopoulos, S., Cavouras, D. and Nikiforidis, G. (July 2009). A comparative study of individual and ensemble majority vote cDNA microarray image segmentation schemes, originating from a spot-adjustable based restoration framework. Computer Methods and Programs in Biomedicine. 95(1). pp. 72-88. Elsevier Ireland Ltd: 2009. Available from: http://www.sciencedirect.com/science/article/pii/S016926070900039X [Accessed 10/03/2009]	en
heal.abstract	The aim of this study was to comparatively evaluate the performances of various segmentation algorithms, in conjunction with a noise reduction step, for gene expression levels intensity extraction in cDNA microarray images. Different segmentation algorithms, based on histogram and unsupervised classification methods, which have never been previously employed in microarray image analysis, were employed either individually or in ensemble majority vote structures for separating spot-images from background pixels. The performances of segmentation algorithms or ensemble structures were evaluated by assessing the validity and reproducibility of gene expression levels extraction in simulated and real cDNA microarray images. By processing high quality simulated images, the highest segmentation accuracy was achieved by an ensemble structure (Histogram Concavity, Gaussian Kernelized Fuzzy-C-Means, Seeded Region Growing). Optimum performance in terms of processing time and segmentation precision for low quality simulated and replicated real cDNA microarray images was attained by the Histogram Concavity algorithm.	en
heal.publisher	Elsevier Ireland Ltd	en
heal.journalName	Computer Methods and Programs in Biomedicine	en
heal.journalType	peer-reviewed
heal.fullTextAvailability	true