A semantically-aided approach for online annotation and retrieval of medical images

Kyriazos, GK; Gerostathopoulos, IT; Kolias, VD; Stoitsis, JS; Nikita, KS

dc.contributor.author	Kyriazos, GK	en
dc.contributor.author	Gerostathopoulos, IT	en
dc.contributor.author	Kolias, VD	en
dc.contributor.author	Stoitsis, JS	en
dc.contributor.author	Nikita, KS	en
dc.date.accessioned	2014-03-01T02:47:15Z
dc.date.available	2014-03-01T02:47:15Z
dc.date.issued	2011	en
dc.identifier.issn	1557170X	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/33032
dc.subject.other	Customizable	en
dc.subject.other	Information contents	en
dc.subject.other	Intelligent search mechanisms	en
dc.subject.other	Keyword search	en
dc.subject.other	Knowledge integration	en
dc.subject.other	Medical experts	en
dc.subject.other	Medical images	en
dc.subject.other	Medical practice	en
dc.subject.other	Online annotation	en
dc.subject.other	Remote access	en
dc.subject.other	Semantic content	en
dc.subject.other	Service Oriented	en
dc.subject.other	Biology	en
dc.subject.other	Interoperability	en
dc.subject.other	Knowledge representation	en
dc.subject.other	Medicine	en
dc.subject.other	Ontology	en
dc.subject.other	Search engines	en
dc.subject.other	Semantic Web	en
dc.subject.other	Medical imaging	en
dc.title	A semantically-aided approach for online annotation and retrieval of medical images	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/IEMBS.2011.6090662	en
heal.identifier.secondary	http://dx.doi.org/10.1109/IEMBS.2011.6090662	en
heal.identifier.secondary	6090662	en
heal.publicationDate	2011	en
heal.abstract	The need for annotating the continuously increasing volume of medical image data is recognized from medical experts for a variety of purposes, regardless if this is medical practice, research or education. The rich information content latent in medical images can be made explicit and formal with the use of well-defined ontologies. Evolution of the Semantic Web now offers a unique opportunity of a web-based, service-oriented approach. Remote access to FMA and ICD-10 reference ontologies provides the ontological annotation framework. The proposed system utilizes this infrastructure to provide a customizable and robust annotation procedure. It also provides an intelligent search mechanism indicating the advantages of semantic over keyword search. The common representation layer discussed facilitates interoperability between institutions and systems, while semantic content enables inference and knowledge integration. © 2011 IEEE.	en
heal.journalName	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS	en
dc.identifier.doi	10.1109/IEMBS.2011.6090662	en
dc.identifier.volume	2011	en
dc.identifier.spage	2372	en
dc.identifier.epage	2375	en