Εμφάνιση απλής εγγραφής

dc.contributor.author Αθανασιάδης, Εμμανουήλ el
dc.contributor.author Κάβουρας, Διονύσης Α. el
dc.contributor.author Σπυρίδωνος, Παναγιώτα Π. el
dc.contributor.author Καλατζής, Ιωάννης el
dc.contributor.author Νικηφορίδης, Γεώργιος Σ. el
dc.date.accessioned 2015-05-13T07:58:14Z
dc.date.available 2015-05-13T07:58:14Z
dc.date.issued 2015-05-13
dc.identifier.uri http://hdl.handle.net/11400/10282
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/10.1007/978-3-540-74272-2_107 en
dc.subject Microarrays
dc.subject Gridding
dc.subject Μικροσυστοιχίες
dc.subject Πλέγμα
dc.title An automatic microarray image gridding technique based on continuous wavelet transform en
heal.type conferenceItem
heal.generalDescription Proceedings 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.identifier.secondary DOI 10.1007/978-3-540-74272-2_107
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 Athanasiadis, E., Cavouras, D., Spyridonos, P., Kalatzis, I. and Nikiforidis, G. (2007). An automatic microarray image gridding technique based on continuous wavelet transform. Proceedings of the 12th International Conference of Computer Analysis of Images and Patterns. Vienna, Austria, 27th-29th August 2007. pp. 864-870. Springer Berlin Heidelberg: 2007. Available from: http://link.springer.com/chapter/10.1007/978-3-540-74272-2_107 en
heal.abstract In the present study, a new gridding method based on continuous wavelet transform (CWT) was performed. Line profiles of x and y axis were calculated, resulting to 2 different signals. These signals were independently processed by means of CWT at 15 different levels, using daubechies 4 mother wavelet. A summation, point by point, was performed on the processed signals, in order to suppress noise and enhance spot’s differences. Additionally, a wavelet based hard thresholding filter was applied to each signal for the task of alleviating the noise of the signals. 14 real microarray images were used in order to visually assess the performance of our gridding method. Each microarray image contained 4 sub-arrays, each sub-array 40x40 spots, thus, 6400 spots totally. Moreover, these images contained contamination areas. According to our results, the accuracy of our algorithm was 98% in all 14 images and in all spots. Additionally, processing time was less than 3 sec on a 1024×1024×16 microarray image, rendering the method a promising technique for an efficient and fully automatic gridding processing. en
heal.publisher Springer Berlin Heidelberg en
heal.fullTextAvailability true
heal.conferenceName International Conference of Computer Analysis of Images and Patterns en
heal.conferenceItemType full paper


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Εμφάνιση απλής εγγραφής

Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες Εκτός από όπου ορίζεται κάτι διαφορετικό, αυτή η άδεια περιγράφεται ως Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες