Multi-level analysis and information extraction considerations for validating 4D models of human function

Marias, K; Dionysiou, DD; Stamatakos, GS; Zacharopoulou, F; Georgiadi, E; Margaritis, T; Maris, TG; Tollis, IG

dc.contributor.author	Marias, K	en
dc.contributor.author	Dionysiou, DD	en
dc.contributor.author	Stamatakos, GS	en
dc.contributor.author	Zacharopoulou, F	en
dc.contributor.author	Georgiadi, E	en
dc.contributor.author	Margaritis, T	en
dc.contributor.author	Maris, TG	en
dc.contributor.author	Tollis, IG	en
dc.date.accessioned	2014-03-01T02:44:50Z
dc.date.available	2014-03-01T02:44:50Z
dc.date.issued	2007	en
dc.identifier.issn	03029743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31971
dc.subject	Biomedical data analysis	en
dc.subject	Modeling	en
dc.subject	Virtual physiological human	en
dc.subject.other	Computer simulation	en
dc.subject.other	Image analysis	en
dc.subject.other	Medical computing	en
dc.subject.other	Miniature automobiles	en
dc.subject.other	Pathology	en
dc.subject.other	Patient treatment	en
dc.subject.other	Biomedical data analysis	en
dc.subject.other	Information extraction	en
dc.subject.other	Virtual physiological human	en
dc.subject.other	Information retrieval	en
dc.title	Multi-level analysis and information extraction considerations for validating 4D models of human function	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/978-3-540-73321-8_81	en
heal.identifier.secondary	http://dx.doi.org/10.1007/978-3-540-73321-8_81	en
heal.publicationDate	2007	en
heal.abstract	Recent research trends focus on how multiscale biomedical information can be modeled and transformed into knowledge, in order to lead to a less interfering but also more individualized diagnosis and therapy. In order to assess the clinical importance of models of human pathology (e.g. cancer), it is necessary to validate them with prior and post treatment clinical data which in turn requires the determination of the tumor size and shape with high resolution, accuracy and precision, as well as structural and physiological information. This paper discusses some of the most important image analysis challenges in order to define an optimal method for extracting more accurate and precise anatomical and functional information related to the underlying pathology, which can be used for initializing and validating models of pathophysiology as well as simulations/predictions of the response to therapeutical regimes. © Springer-Verlag Berlin Heidelberg 2007.	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
dc.identifier.doi	10.1007/978-3-540-73321-8_81	en
dc.identifier.volume	4561 LNCS	en
dc.identifier.spage	703	en
dc.identifier.epage	709	en