Artificial Immune Network for Automatic Point Correspondence in Medical Images

Delibasis, K; Asvestas, P; Mouravliansky, N; Economopoulos, T; Matsopoulos, G

dc.contributor.author	Delibasis, K	en
dc.contributor.author	Asvestas, P	en
dc.contributor.author	Mouravliansky, N	en
dc.contributor.author	Economopoulos, T	en
dc.contributor.author	Matsopoulos, G	en
dc.date.accessioned	2014-03-01T02:50:57Z
dc.date.available	2014-03-01T02:50:57Z
dc.date.issued	2007	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/35232
dc.subject	Function Optimization	en
dc.subject	Medical Image	en
dc.subject	Template Matching	en
dc.title	Artificial Immune Network for Automatic Point Correspondence in Medical Images	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/IEMBS.2007.4352421	en
heal.identifier.secondary	http://dx.doi.org/10.1109/IEMBS.2007.4352421	en
heal.publicationDate	2007	en
heal.abstract	In this work, an automatic method for point-by point correspondence between medical images is presented based on the implementation of an Artificial Immune Network (AIN). AIN is a relatively novel population based algorithm, which when applied to multimodal function optimization exhibit the attractive feature of locating, the global minimum of a function, as well as a large number of strong	en
heal.journalName	Annual International Conference of the IEEE Engineering in Medicine and Biology Society	en
dc.identifier.doi	10.1109/IEMBS.2007.4352421	en