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

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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


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