Relationship between carotid plaque composition and embolization risk assessed by computer processing of ultrasound images

dc.contributor.author	Θεοχαράκης, Παντελής	el
dc.contributor.author	Καλατζής, Ιωάννης	el
dc.contributor.author	Πήλιουρας, Νικόλαος	el
dc.contributor.author	Δημητρόπουλος, Νικόλαος	el
dc.contributor.author	Βεντούρας, Ερρίκος Μ.	el
dc.date.accessioned	2015-01-28T13:24:42Z
dc.date.available	2015-01-28T13:24:42Z
dc.date.issued	2015-01-28
dc.identifier.uri	http://hdl.handle.net/11400/4933
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.subject	Carotid plaque ultrasound images
dc.subject	Pattern recognition
dc.subject	Υπέρηχες εικόνες της καρωτιδικής πλάκας
dc.subject	Αναγνώρισης προτύπων
dc.title	Relationship between carotid plaque composition and embolization risk assessed by computer processing of ultrasound images	en
heal.type	conferenceItem
heal.generalDescription	Proceedings of the International Conference of Computational Methods in Sciences and Enginnering 2003	en
heal.classification	Medicine
heal.classification	Medical technology
heal.classification	Ιατρική
heal.classification	Ιατρικά όργανα και εξοπλισμός
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh00006614
heal.classificationURI	http://skos.um.es/unescothes/C02465
heal.classificationURI	N/A-Ιατρική
heal.classificationURI	N/A-Ιατρικά όργανα και εξοπλισμός
heal.keywordURI	http://skos.um.es/unescothes/C02924
heal.contributorName	Κάβουρας, Διονύσης Α.	el
heal.identifier.secondary	ISBN: 981-238-595-9
heal.language	en
heal.access	campus
heal.recordProvider	Τ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Βιοϊατρικής Τεχνολογίας Τ.Ε.	el
heal.publicationDate	2003
heal.bibliographicCitation	Theocharakis, P., Kalatzis, I., Piliouras, N., Dimitropoulos, N., Ventouras, E., et al. (2003). Relationship between carotid plaque composition and embolization risk assessed by computer processing of ultrasound images. In the International Conference of Computational Methods in Sciences and Enginnering. pp. 626-630. Kastoria, Greece, 2003.	en
heal.abstract	The purpose of this work was to process carotid plaque ultrasound images, employing pattern recognition methods, for assessing the embolization risk factor associated with carotid plaque composition. Carotid plaques of 56 ultrasound images displaying carotid artery stenosis were categorized by means of the gray scale median (GSM) as high risk of causing brain infarcts (GSM≤50 gray level) and low-risk (GSM>50 gray level), and in accordance with the physician’s assessment and final clinical outcome. In each plaque image, the ratio of echo-dense to echo-lucent area was automatically calculated and it was combined with other textural features, calculated from the image histogram, the co-occurrence matrix, and the run-length matrix. These features were employed as input to two classifiers, the quadratic Bayesian (QB accuracy 91.7%) and the support vector machine (SVM accuracy 100%), which were trained to characterize plaques as either high risk or low risk of causing brain infarcts.	en
heal.publisher	[χ.ό.]	el
heal.fullTextAvailability	true
heal.conferenceName	International Conference of Computational Methods in Sciences and Enginnering	en
heal.conferenceItemType	full paper