Treatment planning optimization by quasi-Newton and simulated annealing methods for gamma unit treatment system

H. Z. Shu, Y. L. Yan, X. D. Bao, Y. Fu, L. M. Luo

Research output: Contribution to journalArticle

18 Citations (Scopus)

Abstract

The gamma unit is used to irradiate a target within the brain. During such a treatment many parameters, including the number of shots, the coordinates, the collimator size and the weight associated with each shot, affect the amount of dose delivered to the target volume and to the surrounding normal tissues. Hence it is not easy to determine an appropriate set of these parameters by a trial and error method. For this reason, we present here an optimization method to determine mathematically those parameters. This method is composed of two steps: firstly, a quasi-Newton method is used to deal with the continuous variables such as position and weight of shots; the result obtained at the end of this step then serves as the initial configuration for the next step, in which a simulated annealing method is applied to optimize all the aforementioned parameters. Application of the proposed methods to two examples shows that our optimization algorithm runs in a satisfactory way.

Original languageEnglish (US)
Pages (from-to)2795-2805
Number of pages11
JournalPhysics in Medicine and Biology
Volume43
Issue number10
DOIs
StatePublished - Oct 1998

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simulated annealing
Simulated annealing
newton
planning
shot
Planning
optimization
annealing
Newton-Raphson method
Brain
Tissue
Newton methods
collimators
brain
Weights and Measures
dosage
configurations

ASJC Scopus subject areas

  • Biomedical Engineering
  • Physics and Astronomy (miscellaneous)
  • Radiology Nuclear Medicine and imaging
  • Radiological and Ultrasound Technology

Cite this

Treatment planning optimization by quasi-Newton and simulated annealing methods for gamma unit treatment system. / Shu, H. Z.; Yan, Y. L.; Bao, X. D.; Fu, Y.; Luo, L. M.

In: Physics in Medicine and Biology, Vol. 43, No. 10, 10.1998, p. 2795-2805.

Research output: Contribution to journalArticle

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