Development of a support vector machine-based image analysis system for assessing the thyroid nodule malignancy risk on ultrasound

dc.contributor.author	Τσαντής, Σταύρος	el
dc.contributor.author	Κάβουρας, Διονύσης Α.	el
dc.contributor.author	Καλατζής, Ιωάννης	el
dc.contributor.author	Πήλιουρας, Νικόλαος	el
dc.contributor.author	Δημητρόπουλος, Νικόλαος	el
dc.date.accessioned	2015-04-30T08:23:37Z
dc.date.available	2015-04-30T08:23:37Z
dc.date.issued	2015-04-30
dc.identifier.uri	http://hdl.handle.net/11400/9304
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.umbjournal.org/article/S0301-5629(05)00288-7/abstract	en
dc.source	http://www.sciencedirect.com/science/article/pii/S0301562905002887	en
dc.subject	Classification--Archives
dc.subject	Support vectors machine
dc.subject	Φορείς υποστήριξης μηχανής
dc.subject	Ταξινόμηση
dc.title	Development of a support vector machine-based image analysis system for assessing the thyroid nodule malignancy risk on ultrasound	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/sh85026720
heal.contributorName	Νικηφορίδης, Γεώργιος Χ.	el
heal.identifier.secondary	DOI: http://dx.doi.org/10.1016/j.ultrasmedbio.2005.07.009
heal.language	en
heal.access	campus
heal.recordProvider	Τ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Βιοϊατρικής Τεχνολογίας Τ.Ε.	el
heal.publicationDate	2005
heal.bibliographicCitation	Tsantis, S., Cavouras, D., Kalatzis, I., Piliouras, N., Dimitropoulos, N., et al. (November 2005). Development of a support vector machine-based image analysis system for assessing the thyroid nodule malignancy risk on ultrasound. Ultrasound in Medicine and Biology. 31(11). pp. 1451-1459. Elsevier Inc: 2005. Available from: http://www.sciencedirect.com/science/article/pii/S0301562905002887 [Accessed 9/11/2005]	en
heal.abstract	An SVM-based image analysis system was developed for assessing the malignancy risk of thyroid nodules. Ultrasound images of 120 cytology confirmed thyroid nodules (78 low-risk and 42 high-risk of malignancy) were manually segmented by a physician using a custom developed software in C++. From each nodule, 40 textural features were automatically calculated and were used with the SVM algorithm in the design of the image analysis system. Highest classification accuracy was 96.7%, misdiagnosing two high-risk and two low-risk thyroid nodules. The proposed system may be of value to physicians as a second opinion tool for avoiding unnecessary invasive procedures.	en
heal.publisher	Elsevier Inc	en
heal.journalName	Ultrasound in Medicine & Biology	en
heal.journalType	peer-reviewed
heal.fullTextAvailability	true