Application of multiobjective genetic algorithms in anatomy based dose optimization in brachytherapy and its comparation with deterministic algorithms

Milickovic, N; Lahanas, M; Papagiannopoulou, M; Karouzakis, K; Baltas, D; Zamboglou, N

dc.contributor.author	Milickovic, N	en
dc.contributor.author	Lahanas, M	en
dc.contributor.author	Papagiannopoulou, M	en
dc.contributor.author	Karouzakis, K	en
dc.contributor.author	Baltas, D	en
dc.contributor.author	Zamboglou, N	en
dc.date.accessioned	2014-03-01T02:49:02Z
dc.date.available	2014-03-01T02:49:02Z
dc.date.issued	2001	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/34251
dc.subject	Aggregation Function	en
dc.subject	Genetic Algorithm	en
dc.subject	Hybrid Algorithm	en
dc.subject	Individual Object	en
dc.subject	multiobjective evolutionary algorithm	en
dc.subject	multiobjective genetic algorithm	en
dc.subject	Multiple Objectives	en
dc.subject	Optimal Algorithm	en
dc.subject	Optimal Method	en
dc.subject	Optimization Problem	en
dc.subject	Satisfiability	en
dc.subject	Dose Volume Histogram	en
dc.subject	High Dose Rate	en
dc.title	Application of multiobjective genetic algorithms in anatomy based dose optimization in brachytherapy and its comparation with deterministic algorithms	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/IEMBS.2001.1019698	en
heal.identifier.secondary	http://dx.doi.org/10.1109/IEMBS.2001.1019698	en
heal.publicationDate	2001	en
heal.abstract	In high dose rate (HDR) brachytherapy the conventional dose optimization algorithms consider the multiple objectives in the form of an aggregate function which combines individual objectives into a single utility value. As a result, the optimization problem becomes a single objective, prior to optimization. Up to 300 parameters must be optimized, satisfying objectives which are often competing. We use multiobjective	en
heal.journalName	Annual International Conference of the IEEE Engineering in Medicine and Biology Society	en
dc.identifier.doi	10.1109/IEMBS.2001.1019698	en