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Inverse treatment planning by simulated annealing optimization of a dose-volume objective function

An algorithm for optimization of numerous modulated beam weights has been developed. This algorithm employs a penalty function theorem and a simulated annealing (SA) routine to model a large-scale constrained optimization problem incorporating dose and dose volume constraints in reflecting the goal of inverse treatment planning by sparing sufficient healthy tissues while delivering a necessary tumorcidal dose. The convergence property of the dose-volume SA algorithm is investigated for validation. Its performance is also evaluated by comparing the algorithm with a gradient technique minimizing the same dose-volume objective function that incorporates the target dose objectives and organ dose-volume constraints by the penalty functions. The comparison shows that the objective function exhibits a global valley in which multiple local minima with similar outcomes in terms of the function values, the dose-volume histograms, and the dose distributions exist. Thus, the gradient algorithm is preferred for this optimization approach due to its fast efficiency.

Identiferoai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.33837
Date January 2001
CreatorsSham, Edwin O. H.
ContributorsHristov, Dimitre (advisor)
PublisherMcGill University
Source SetsLibrary and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada
LanguageEnglish
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Formatapplication/pdf
CoverageMaster of Science (Department of Medical Radiation Physics.)
RightsAll items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated.
Relationalephsysno: 001863629, proquestno: MQ78955, Theses scanned by UMI/ProQuest.

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