Please use this identifier to cite or link to this item: http://hdl.handle.net/11400/10372
Full metadata record
DC FieldValueLanguage
dc.contributor.authorΑθανασιάδης, Εμμανουήλ Ι.ell
dc.contributor.authorΓκλώτσος, Δημήτριοςell
dc.contributor.authorΔασκαλάκης, Αντώνηςell
dc.contributor.authorΜπουγιούκος, Παναγιώτηςell
dc.contributor.authorΚωστόπουλος, Σπυρίδωνell
dc.date.accessioned2015-05-14T15:08:47Z-
dc.date.available2015-05-14T15:08:47Z-
dc.date.issued2015-05-14-
dc.date.issued2006-
dc.identifier.citationAthanasiadis, E., Glotsos, D., Daskalakis, A., Bougioukos, P., Kostopoulos, S., et al. (2006). Microarray image enhancement techniques using the discrete wavelet transform. In the 2nd International Conference "From Scientific Computing to Computational Engineering" (2nd IC-SCCE 2006). Athens, 5th – 8th July, 2006. Available from: http://www.bme.teiath.gr/medisp/pdfs/ATHANASSIADIS_2006_SCCE_Microarray%20Image%20Enhancement.pdfeng
dc.identifier.urihttp://hdl.handle.net/11400/10372-
dc.description.abstractThe objective of this work was to perform a comparative evaluation of five different wavelet-based filtering techniques in the task of microarray image denoising and enhancement. Clinical material comprised microarray images collected from the Oak Ridge National Laboratory. Image processing was performed in two stages: In the first stage an Exponential Histogram Equalization filter was applied in order to increase the contrast between spots and surrounding background. In the second stage, five wavelet-based image filters (Simple Piece-Wise Linear Mapping Filter (SPWLMF), Hard Threshold filter (HTF), Wavelet Enhancement with Noise Suppression filter (WEWNSF), Garrote Wavelet Threshold filter (GWTF) and Sigmoidal Non-linear Enhancement filter (SNLEF)) were implemented for denoising and enhancing gene microarray spots. The enhancing effectiveness of the five filters was assessed by calculating the Mean-Square-Error (MSE) and the Signal-to-MSE ratio. Results showed that the image quality of the processed images was superior to that of the original images. Significant noise suppression was accomplished by the SPWLMP filter, which scored the minimum MSE and the maximum Signal-to-MSE ratio. Processing time was less than 3 seconds for 512x512 sample images. Wavelet-based processing of microarray images was found to enhance microarray images effectively, by improving the visualization of spots and by suppressing image noise.eng
dc.language.isoeng-
dc.rightsΑναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.sourcehttp://www.bme.teiath.gr/medisp/pdfs/ATHANASSIADIS_2006_SCCE_Microarray%20Image%20Enhancement.pdfen
dc.subjectMicroarray-
dc.subjectWavelets (Mathematics)-
dc.subjectΜικροσυστοιχίες-
dc.subjectΚυμάτιο-
dc.titleMicroarray image enhancement techniques using the discrete wavelet transformeng
dc.typeΔημοσίευση σε συνέδριο-
heal.classificationTechnology-
heal.classificationComputer science-
heal.classificationΤεχνολογία-
heal.classificationΠληροφορική-
heal.classificationURIhttp://zbw.eu/stw/descriptor/10470-6-
heal.classificationURIhttp://data.seab.gr/concepts/77de68daecd823babbb58edb1c8e14d7106e83bb-
heal.classificationURI**N/A**-Τεχνολογία-
heal.classificationURI**N/A**-Πληροφορική-
heal.keywordURIhttp://id.loc.gov/authorities/subjects/sh91006163-
heal.contributorNameΘεοχαράκης, Παντελήςell
heal.contributorNameΣπυρίδωνος, Παναγιώτα Π.ell
heal.contributorNameΚαλατζής, Ιωάννηςell
heal.contributorNameΝικηφορίδης, Γεώργιος Σ.ell
heal.contributorNameΚάβουρας, Διονύσης Α.ell
heal.accessfree-
heal.recordProviderΤ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Βιοϊατρικής Τεχνολογίας Τ.Ε.ell
heal.fullTextAvailabilitytrue-
heal.conferenceNameInternational Conference "From Scientific Computing to Computational Engineering"eng
heal.conferenceItemTypefull paper-
Appears in Collections:Δημοσιεύσεις

Files in This Item:
File Description SizeFormat 
Microarray Image Enhancement Techniques Using the Discrete Wavelet Transform.pdf396.7 kBAdobe PDFView/Open


This item is licensed under a Creative Commons License Creative Commons