Quantitative combination of volumetric MR imaging and MR spectroscopy data for the discrimination of meningiomas from metastatic brain tumors by means of pattern recognition

dc.contributor.author	Γεωργιάδης, Παντελής	el
dc.contributor.author	Κωστόπουλος, Σπυρίδων	el
dc.contributor.author	Κάβουρας, Διονύσης Α.	el
dc.contributor.author	Γκλώτσος, Δημήτριος	el
dc.contributor.author	Καλατζής, Ιωάννης	el
dc.date.accessioned	2015-05-04T07:59:26Z
dc.date.available	2015-05-04T07:59:26Z
dc.date.issued	2015-05-04
dc.identifier.uri	http://hdl.handle.net/11400/9612
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.mrijournal.com/article/S0730-725X(10)00398-X/abstract	en
dc.source	http://www.sciencedirect.com/science/article/pii/S0730725X1000398X	en
dc.subject	Brain--Tumors
dc.subject	Magnetic resonance imaging
dc.subject	Εγκεφαλικός όγκος
dc.subject	Μαγνητική τομογραφία
dc.title	Quantitative combination of volumetric MR imaging and MR spectroscopy data for the discrimination of meningiomas from metastatic brain tumors by means of pattern recognition	en
heal.type	journalArticle
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.keywordURI	http://id.loc.gov/authorities/subjects/sh85016351
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh85079741
heal.contributorName	Σηφάκη, Κοραλία	el
heal.contributorName	Μάλαμας, Μενέλαος	el
heal.contributorName	Σολωμού, Αικατερίνη	el
heal.contributorName	Νικηφορίδης, Γεώργιος Χ.	el
heal.identifier.secondary	doi:10.1016/j.mri.2010.11.006
heal.language	en
heal.access	campus
heal.recordProvider	Τ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Βιοϊατρικής Τεχνολογίας Τ.Ε.	el
heal.publicationDate	2011
heal.bibliographicCitation	Georgiadis, P., Kostopoulos, S., Cavouras, D., Glotsos, D., Kalatzis, I., et al. (May 2011). Quantitative combination of volumetric MR imaging and MR spectroscopy data for the discrimination of meningiomas from metastatic brain tumors by means of pattern recognition. Magnetic Resonance Imaging. 29(4). pp. 525-535. Elsevier Inc: 2011. Available from: http://www.sciencedirect.com/science/article/pii/S0730725X1000398X [Accessed 11/02/2011]	en
heal.abstract	The analysis of information derived from magnetic resonance imaging (MRI) and spectroscopy (MRS) has been identified as an important indicator for discriminating among different brain pathologies. The purpose of this study was to investigate the efficiency of the combination of textural MRI features and MRS metabolite ratios by means of a pattern recognition system in the task of discriminating between meningiomas and metastatic brain tumors. The data set consisted of 40 brain MR image series and their corresponding spectral data obtained from patients with verified tumors. The pattern recognition system was designed employing the support vector machines classifier with radial basis function kernel; the system was evaluated using an external cross validation process to render results indicative of the generalization performance to “unknown” cases. The combination of MR textural and spectroscopic features resulted in 92.15% overall accuracy in discriminating meningiomas from metastatic brain tumors. The fusion of the information derived from MRI and MRS data might be helpful in providing clinicians a useful second opinion tool for accurate characterization of brain tumors.	en
heal.publisher	Elsevier Inc	en
heal.journalName	Magnetic Resonance Imaging	en
heal.journalType	peer-reviewed
heal.fullTextAvailability	true