Computer aided discrimination between primary and secondary brain tumors
on MRI

dc.contributor.author	Γεωργιάδης, Παντελής	el
dc.contributor.author	Κάβουρας, Διονύσης Α.	el
dc.contributor.author	Καλατζής, Ιωάννης	el
dc.contributor.author	Γκλώτσος, Δημήτριος	el
dc.contributor.author	Σηφάκη, Κοραλία	el
dc.date.accessioned	2015-01-27T08:22:21Z
dc.date.available	2015-01-27T08:22:21Z
dc.date.issued	2015-01-27
dc.identifier.uri	http://hdl.handle.net/11400/4816
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://e-jst.teiath.gr/	en
dc.subject	Volumetric textural features
dc.subject	Χαρακτηριστικά ογκομετρικής υφής
dc.subject	Brain tumors
dc.subject	MRI
dc.subject	Pattern classification
dc.subject	Εγκεφαλικοί όγκοι
dc.subject	Ταξινόμηση μοτίβο
dc.title	Computer aided discrimination between primary and secondary brain tumors on MRI	en
heal.type	journalArticle
heal.secondaryTitle	from 2D to 3D texture analysis	en
heal.classification	Science
heal.classification	Mathematics
heal.classification	Επιστήμες
heal.classification	Μαθηματικά
heal.classificationURI	http://zbw.eu/stw/descriptor/15685-2
heal.classificationURI	http://zbw.eu/stw/thsys/70269
heal.classificationURI	N/A-Επιστήμες
heal.classificationURI	N/A-Μαθηματικά
heal.contributorName	Μάλαμας, Μενέλαος	el
heal.contributorName	Νικηφορίδης, Γεώργιος	el
heal.contributorName	Σολωμού, Αικατερίνη	el
heal.language	en
heal.access	free
heal.publicationDate	2008
heal.bibliographicCitation	Georgiadis, P., Cavouras, D.A., Kalatzis, I., Glotsos, D., Sifaki, K., et al. (2008). Computer aided discrimination between primary and secondary brain tumors on MRI: from 2D to 3D texture analysis. "e-Journal of Science & Technology". [Online] 3(2): 9-18. Available from: http://e-jst.teiath.gr/	en
heal.abstract	Three dimensional texture analysis of volumetric brain MR images have been identified as an important indicator for discriminating among different brain pathologies. The aim of the present study was to evaluate the efficiency of three dimensional textural features using a pattern recognition system in the task of discriminating primary from metastatic brain tissues on T1 post-contrast MRI series. The dataset consisted of sixty seven brain MRI series obtained from patients with verified and untreated intracranial tumors. The pattern recognition system was designed employing a probabilistic neural network classifier, specially modified in order to integrate the non-linear least squares feature transformation logic in its discriminant function. The latter, in conjunction with using three dimensional textural features, enabled boosting up the performance of the system in discriminating primary from metastatic with accuracy of 95.52%. The proposed system might be used as an assisting tool for brain tumor characterization on volumetric MRI series.	en
heal.publisher	Νερατζής, Ηλίας	el
heal.publisher	Σιανούδης, Ιωάννης	el
heal.journalName	e-Journal of Science & Technology	en
heal.journalName	e-Περιοδικό Επιστήμης & Τεχνολογίας	el
heal.journalType	peer-reviewed
heal.fullTextAvailability	true