title: [Genetic algorithm-based dose optimization in intensity modulated radiation therapy].
abstract: As a powerful global optimization approach, genetic algorithms (GA) can solve a variety of optimization problems in which the objective function is discontinuous, non-differentiable, or highly non-linear, to produce high convergence speed and vast search space. In this thesis, GA is used to optimize the beam weights of intensity modulated radiation therapy (IMRT) inverse planning, and 2D and 3D isodose contour as well as dose volume histogram (DVH) are used to evaluate the treatment plan. Also presented in this thesis are the results of calculation with discussions.
authors.affiliation: School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China. gzchou@263.net
authors.forename: Ling-Hong
authors.initials: LH
authors.lastname: Zhou
authors.forename: Mu-Tao
authors.initials: MT
authors.lastname: Tang
authors.forename: Zhuo-Yu
authors.initials: ZY
authors.lastname: Wang
authors.forename: Chao-Min
authors.initials: CM
authors.lastname: Chen
authors.forename: Qing-Wen
authors.initials: QW
authors.lastname: Lü
authors.forename: Hao-Yu
authors.initials: HY
authors.lastname: Jin
mesh_terms: D000465:Algorithms; D006801:Humans; D008962:Models, Theoretical; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D020266:Radiotherapy, Conformal / Q000379:methods* / Q000592:standards