Physics in Medicine and Biology · 1998 · 118 citations · 9 references
MedicineRadiation OncologyClinical Radiation OncologyOptimizationTreatment PlanningEvolutionary OptimizationGenetic AlgorithmsGeometric OptimizationIntensity-modulated RadiotherapyRadiation TherapyRadiation Treatment PlanningGenetic Algorithm OptimizationGenetic Algorithms For SearchHybrid Genetic AlgorithmsIntensity ModulationMultiobjective Genetic AlgorithmsRadiotherapy Dose PlanningTreatment Plan OptimizationTreatment Planning Optimization
This paper proposes a new geometrical formulation of the coplanar beam orientation problem combined with a hybrid multiobjective genetic algorithm. The approach is demonstrated by optimizing the beam orientation in two dimensions, with the objectives being formulated using planar geometry. The traditional formulation of the objectives associated with the organs at risk has been modified to account for the use of complex dose delivery techniques such as beam intensity modulation. The new algorithm attempts to replicate the approach of a treatment planner whilst reducing the amount of computation required. Hybrid genetic search operators have been developed to improve the performance of the genetic algorithm by exploiting problem-specific features. The multiobjective genetic algorithm is formulated around the concept of Pareto optimality which enables the algorithm to search in parallel for different objectives. When the approach is applied without constraining the number of beams, the solution produces an indication of the minimum number of beams required. It is also possible to obtain non-dominated solutions for various numbers of beams, thereby giving the clinicians a choice in terms of the number of beams as well as in the orientation of these beams.
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Number and orientations of beams in intensity‐modulated radiation treatments
Jörg Stein, R Mohan, Xiaohong Wang et al. · Medical Physics · 1997 · 274 citations · Full text