Hybrid optimisation technique for radiotherapy treatment planning

Olivier C.L. Haas; Keith J. Burnham; John A. Mills

doi:10.1109/CCA.1998.728450

Hybrid optimisation technique for radiotherapy treatment planning

Olivier C.L. Haas, Keith J. Burnham, John A. Mills

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding

4 Citations (Scopus)

Abstract

Presents an optimisation strategy, based on a hybrid multi-objective genetic algorithm, to automate the planning of traditional radiotherapy treatment. The optimisation algorithm is formulated around the concept of Pareto optimality to exploit a population based search procedure thereby considering each of the objectives independently. It explores the solutions belonging to the Pareto optimal set prior to concentrating on the best regions of the search space. Once the Pareto optimal set has been determined, a posteriori articulation of the objectives is used to provide the clinicians with a few alternative solutions, all of them non-dominated and therefore mathematically optimal, leaving the final decision to the clinicians

Original language	English
Title of host publication	Proceedings of the 1998 IEEE International Conference on Control Applications
Publisher	IEEE
Pages	368-372
Volume	1
ISBN (Print)	0-7803-4104-X
DOIs	https://doi.org/10.1109/CCA.1998.728450
Publication status	Published - 1 Sept 1998

Bibliographical note

This conference paper is not yet available on the repository. The paper was given at the 1998 IEEE International Conference on Control Applications, Trieste, Italy, 1-4 September 1998

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10.1109/CCA.1998.728450

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@inproceedings{7cae76cc1b814e64be20ef5682236348,

title = "Hybrid optimisation technique for radiotherapy treatment planning",

abstract = "Presents an optimisation strategy, based on a hybrid multi-objective genetic algorithm, to automate the planning of traditional radiotherapy treatment. The optimisation algorithm is formulated around the concept of Pareto optimality to exploit a population based search procedure thereby considering each of the objectives independently. It explores the solutions belonging to the Pareto optimal set prior to concentrating on the best regions of the search space. Once the Pareto optimal set has been determined, a posteriori articulation of the objectives is used to provide the clinicians with a few alternative solutions, all of them non-dominated and therefore mathematically optimal, leaving the final decision to the clinicians",

author = "Haas, {Olivier C.L.} and Burnham, {Keith J.} and Mills, {John A.}",

note = "This conference paper is not yet available on the repository. The paper was given at the 1998 IEEE International Conference on Control Applications, Trieste, Italy, 1-4 September 1998",

year = "1998",

month = sep,

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doi = "10.1109/CCA.1998.728450",

language = "English",

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TY - GEN

T1 - Hybrid optimisation technique for radiotherapy treatment planning

AU - Haas, Olivier C.L.

AU - Burnham, Keith J.

AU - Mills, John A.

N1 - This conference paper is not yet available on the repository. The paper was given at the 1998 IEEE International Conference on Control Applications, Trieste, Italy, 1-4 September 1998

PY - 1998/9/1

Y1 - 1998/9/1

N2 - Presents an optimisation strategy, based on a hybrid multi-objective genetic algorithm, to automate the planning of traditional radiotherapy treatment. The optimisation algorithm is formulated around the concept of Pareto optimality to exploit a population based search procedure thereby considering each of the objectives independently. It explores the solutions belonging to the Pareto optimal set prior to concentrating on the best regions of the search space. Once the Pareto optimal set has been determined, a posteriori articulation of the objectives is used to provide the clinicians with a few alternative solutions, all of them non-dominated and therefore mathematically optimal, leaving the final decision to the clinicians

AB - Presents an optimisation strategy, based on a hybrid multi-objective genetic algorithm, to automate the planning of traditional radiotherapy treatment. The optimisation algorithm is formulated around the concept of Pareto optimality to exploit a population based search procedure thereby considering each of the objectives independently. It explores the solutions belonging to the Pareto optimal set prior to concentrating on the best regions of the search space. Once the Pareto optimal set has been determined, a posteriori articulation of the objectives is used to provide the clinicians with a few alternative solutions, all of them non-dominated and therefore mathematically optimal, leaving the final decision to the clinicians

U2 - 10.1109/CCA.1998.728450

DO - 10.1109/CCA.1998.728450

M3 - Conference proceeding

SN - 0-7803-4104-X

VL - 1

SP - 368

EP - 372

BT - Proceedings of the 1998 IEEE International Conference on Control Applications

PB - IEEE

ER -

Hybrid optimisation technique for radiotherapy treatment planning

Abstract

Bibliographical note

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