Optimization of beam orientation in radiotherapy using planar geometry
Optimization of beam orientation in radiotherapy using planar geometry
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DOI：
10.1088/0031-9155/43/8/013
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发表时间：
1998-08-01
影响因子：
3.5
通讯作者：
Mills, JA
中科院分区：
文献类型：
--
作者：
Haas, OCL;Burnham, KJ;Mills, JA
本文提出了一种新的共面波束定向问题的几何表述与混合多目标遗传算法相结合。该方法是通过优化在两个维度上的光束方向，与目标制定使用平面几何。与危险器官相关的目标的传统公式已被修改，以考虑使用复杂的剂量输送技术，如光束强度调制。新算法试图复制治疗计划者的方法，同时减少所需的计算量。混合遗传搜索算子已经开发，以提高遗传算法的性能，利用特定问题的功能。多目标遗传算法的帕累托最优的概念，使算法能够并行搜索不同的目标制定。当应用该方法而不限制梁的数量时，该解决方案会产生所需梁的最小数量的指示。还可以获得针对各种数量的射束的非支配解，从而在射束的数量以及这些射束的取向方面给予临床医生选择。
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 nondominated 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.