Please use this identifier to cite or link to this item: http://hdl.handle.net/11400/10115
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dc.contributor.authorΓκλώτσος, Δημήτριοςell
dc.contributor.authorΡαβαζούλα, Παναγιώταell
dc.contributor.authorΚάβουρας, Διονύσης Α.ell
dc.contributor.authorΝικηφορίδης, Γεώργιος Χ.ell
dc.contributor.authorTohka, Jussieng
dc.date.accessioned2015-05-11T08:56:39Z-
dc.date.issued2015-05-11-
dc.date.issued2005-
dc.identifier.citationGlotsos, D., Tohka, J., Ravazoula, P., Cavouras, D. and Nikiforidis, G. (February & April 2005). Automated diagnosis of brain tumours astrocytomas using probabilistic neural network clustering and support vector machines. International Journal of Neural Systems. 15(01n02). pp. 1-11. World Scientific Publishing: 2005.eng
dc.identifier.urihttp://hdl.handle.net/11400/10115-
dc.description.abstractA computer-aided diagnosis system was developed for assisting brain astrocytomas malignancy grading. Microscopy images from 140 astrocytic biopsies were digitized and cell nuclei were automatically segmented using a Probabilistic Neural Network pixel-based clustering algorithm. A decision tree classification scheme was constructed to discriminate low, intermediate and high-grade tumours by analyzing nuclear features extracted from segmented nuclei with a Support Vector Machine classifier. Nuclei were segmented with an average accuracy of 86.5%. Low, intermediate, and high-grade tumours were identified with 95%, 88.3%, and 91% accuracies respectively. The proposed algorithm could be used as a second opinion tool for the histopathologists.eng
dc.language.isoeng-
dc.publisherWorld Scientific Publishingeng
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.worldscientific.com/doi/abs/10.1142/S0129065705000013en
dc.subjectProbabilistic neural network-
dc.subjectMicroscopy-
dc.subjectΠιθανοτικό νευρωνικό δίκτυο-
dc.subjectΜικροσκοπία-
dc.titleAutomated diagnosis of brain tumours astrocytomas using probabilistic neural network clustering and support vector machineseng
dc.typeΔημοσίευση σε περιοδικό-
heal.classificationMedicine-
heal.classificationBiomedical engineering-
heal.classificationΙατρική-
heal.classificationΒιοϊατρική τεχνολογία-
heal.classificationURIhttp://id.loc.gov/authorities/subjects/sh00006614-
heal.classificationURIhttp://id.loc.gov/authorities/subjects/sh85014237-
heal.classificationURI**N/A**-Ιατρική-
heal.classificationURI**N/A**-Βιοϊατρική τεχνολογία-
heal.keywordURIhttp://skos.um.es/unesco6/230112-
heal.identifier.secondaryDOI: 10.1142/S0129065705000013-
heal.dateAvailable10000-01-01-
heal.accessembargo-
heal.recordProviderΤ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Βιοϊατρικής Τεχνολογίας Τ.Ε.ell
heal.journalNameInternational Journal of Neural Systemseng
heal.journalTypepeer-reviewed-
heal.fullTextAvailabilityfalse-
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