Genes expression level quantification using a spot-based algorithmic pipeline

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	Γεωργιάδης, Παντελής	el
dc.date.accessioned	2015-05-14T14:41:39Z
dc.date.issued	2015-05-14
dc.identifier.uri	http://hdl.handle.net/11400/10371
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.ncbi.nlm.nih.gov/pubmed/18002165	en
dc.source	http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4352499	en
dc.subject	Gene
dc.subject	Microarray images
dc.subject	Γονίδιο
dc.subject	Εικόνες μικροσυστοιχιών
dc.title	Genes expression level quantification using a spot-based algorithmic pipeline	en
heal.type	conferenceItem
heal.generalDescription	Proceedings	en
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	Καλατζής, Ιωάννης	el
heal.contributorName	Καγκάδης, Γεώργιος Χ.	el
heal.contributorName	Νικηφορίδης, Γεώργιος Σ.	el
heal.identifier.secondary	DOI: 10.1109/IEMBS.2007.4352499
heal.dateAvailable	10000-01-01
heal.language	en
heal.access	forever
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., Georgiadis, P., et al. (2007). Genes expression level quantification using a spot-based algorithmic pipeline. Proceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. pp. 1148–1151. France, Lyon, 23th-26th August, 2007. IEEE: 2007.	en
heal.abstract	An efficient spot-based (SB) algorithmic pipeline of clustering, enhancement, and segmentation techniques was developed to quantify gene expression levels in microarray images. The SB-pipeline employed i/a griding procedure to locate spot-regions, ii/a clustering algorithm (enhanced fuzzy c- means or EnFCM) to roughly segment spots from background and estimate background noise and spot's center, iii/an adaptive histogram modification technique to accentuate spot's boundaries, and iv/a segmentation algorithm (Seeded Region Growing or SRG), to extract microarray spots' intensities. Extracted intensities were comparatively evaluated in term of Mean Absolute Error (MAE) against the MAGIC TOOL's SRG employing a dataset of 7 replicated microarray images (6400 spots each). MAE box-plots mean values were 0.254 and 0.630 for the SB-pipeline and the MAGIC TOOL respectively. Total processing times for the dataset evaluated (7 images) were 2100 seconds and 3410 seconds for the SB-pipeline and MAGIC TOOL respectively.	en
heal.publisher	IEEE	en
heal.fullTextAvailability	true
heal.conferenceName	Annual International Conference of the IEEE Engineering in Medicine and Biology Society	en
heal.conferenceItemType	full paper