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.
Subject(s)
Humans , Algorithms , Models, Theoretical , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted , Methods , Radiotherapy, Conformal , Methods , Reference StandardsABSTRACT
<p><b>UNLABELLED</b>To study the method for dose calculation and beam weight optimization of intensity-modulated radiation therapy (IMRT).</p><p><b>METHODS</b>The IMRT dose calculation model based on two-dimensional convolution was constructed, the program of dose calculation and beam weight optimization with genetic algorithm was written with Visual c#.Net, and the optimization results were analyzed.</p><p><b>RESULTS</b>Genetic algorithm optimization of beam weights can produce highly conformal dose distributions within a clinically acceptable computation time.</p><p><b>CONCLUSION</b>Genetic algorithm is valid and efficient in IMRT beam weight optimization, which may facilitate IMRT treatment planning.</p>