Genetic Algorithm Applied to Radiotherapy Treatment Planning

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

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

Abstract

Conformal therapy attempts to produce accurate medical treatment that will produce a uniform dose over cancerous regions whilst at the same time sparing healthy tissues, especially the organs at risk. The constrained optimisation problem, that consists of working back from a given dose specification to elemental beam weight intensities is referred as the so called inverse problem. Due to the nature of the problem and in particular to its conflicting objectives, it is believed that heuristic techniques may have advantages over direct methods to solve for the beam intensities.
Original languageEnglish
Title of host publicationArtificial Neural Nets and Genetic Algorithms: Proceedings of the International Conference in Alès, France, 1995
EditorsD.W. Pearson, N. C. Steele, R. F. Albrecht
Place of PublicationVienna, Austria
PublisherSpringer Verlag
Pages432-435
Number of pages4
ISBN (Print)978-3-211-82692-8
DOIs
Publication statusPublished - 1995

Fingerprint

genetic algorithms
planning
radiation therapy
dosage
organs
specifications
therapy
optimization

Bibliographical note

This conference paper is not available on the repository. The paper was given at the Artificial Neural Nets and Genetic Algorithms International Conference in Alès, France, 1995

Keywords

  • Artificial Intelligence (incl. Robotics)
  • Business Information Systems
  • Complexity
  • Information Storage and Retrieval
  • Data Storage Representation
  • Memory Structures

Cite this

Haas, O. C. L., Burnham, K. J., Fisher, M. H., & Mills, J. A. (1995). Genetic Algorithm Applied to Radiotherapy Treatment Planning. In D. W. Pearson, N. C. Steele, & R. F. Albrecht (Eds.), Artificial Neural Nets and Genetic Algorithms: Proceedings of the International Conference in Alès, France, 1995 (pp. 432-435). Vienna, Austria: Springer Verlag. https://doi.org/10.1007/978-3-7091-7535-4_112

Genetic Algorithm Applied to Radiotherapy Treatment Planning. / Haas, Olivier C.L.; Burnham, Keith J.; Fisher, M.H.; Mills, John A.

Artificial Neural Nets and Genetic Algorithms: Proceedings of the International Conference in Alès, France, 1995. ed. / D.W. Pearson; N. C. Steele; R. F. Albrecht. Vienna, Austria : Springer Verlag, 1995. p. 432-435.

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

Haas, OCL, Burnham, KJ, Fisher, MH & Mills, JA 1995, Genetic Algorithm Applied to Radiotherapy Treatment Planning. in DW Pearson, NC Steele & RF Albrecht (eds), Artificial Neural Nets and Genetic Algorithms: Proceedings of the International Conference in Alès, France, 1995. Springer Verlag, Vienna, Austria, pp. 432-435. https://doi.org/10.1007/978-3-7091-7535-4_112
Haas OCL, Burnham KJ, Fisher MH, Mills JA. Genetic Algorithm Applied to Radiotherapy Treatment Planning. In Pearson DW, Steele NC, Albrecht RF, editors, Artificial Neural Nets and Genetic Algorithms: Proceedings of the International Conference in Alès, France, 1995. Vienna, Austria: Springer Verlag. 1995. p. 432-435 https://doi.org/10.1007/978-3-7091-7535-4_112
Haas, Olivier C.L. ; Burnham, Keith J. ; Fisher, M.H. ; Mills, John A. / Genetic Algorithm Applied to Radiotherapy Treatment Planning. Artificial Neural Nets and Genetic Algorithms: Proceedings of the International Conference in Alès, France, 1995. editor / D.W. Pearson ; N. C. Steele ; R. F. Albrecht. Vienna, Austria : Springer Verlag, 1995. pp. 432-435
@inproceedings{7785148ea9dc4772895d1b74385f079c,
title = "Genetic Algorithm Applied to Radiotherapy Treatment Planning",
abstract = "Conformal therapy attempts to produce accurate medical treatment that will produce a uniform dose over cancerous regions whilst at the same time sparing healthy tissues, especially the organs at risk. The constrained optimisation problem, that consists of working back from a given dose specification to elemental beam weight intensities is referred as the so called inverse problem. Due to the nature of the problem and in particular to its conflicting objectives, it is believed that heuristic techniques may have advantages over direct methods to solve for the beam intensities.",
keywords = "Artificial Intelligence (incl. Robotics), Business Information Systems, Complexity, Information Storage and Retrieval, Data Storage Representation, Memory Structures",
author = "Haas, {Olivier C.L.} and Burnham, {Keith J.} and M.H. Fisher and Mills, {John A.}",
note = "This conference paper is not available on the repository. The paper was given at the Artificial Neural Nets and Genetic Algorithms International Conference in Al{\`e}s, France, 1995",
year = "1995",
doi = "10.1007/978-3-7091-7535-4_112",
language = "English",
isbn = "978-3-211-82692-8",
pages = "432--435",
editor = "D.W. Pearson and Steele, {N. C.} and Albrecht, {R. F.}",
booktitle = "Artificial Neural Nets and Genetic Algorithms: Proceedings of the International Conference in Al{\`e}s, France, 1995",
publisher = "Springer Verlag",
address = "Austria",

}

TY - GEN

T1 - Genetic Algorithm Applied to Radiotherapy Treatment Planning

AU - Haas, Olivier C.L.

AU - Burnham, Keith J.

AU - Fisher, M.H.

AU - Mills, John A.

N1 - This conference paper is not available on the repository. The paper was given at the Artificial Neural Nets and Genetic Algorithms International Conference in Alès, France, 1995

PY - 1995

Y1 - 1995

N2 - Conformal therapy attempts to produce accurate medical treatment that will produce a uniform dose over cancerous regions whilst at the same time sparing healthy tissues, especially the organs at risk. The constrained optimisation problem, that consists of working back from a given dose specification to elemental beam weight intensities is referred as the so called inverse problem. Due to the nature of the problem and in particular to its conflicting objectives, it is believed that heuristic techniques may have advantages over direct methods to solve for the beam intensities.

AB - Conformal therapy attempts to produce accurate medical treatment that will produce a uniform dose over cancerous regions whilst at the same time sparing healthy tissues, especially the organs at risk. The constrained optimisation problem, that consists of working back from a given dose specification to elemental beam weight intensities is referred as the so called inverse problem. Due to the nature of the problem and in particular to its conflicting objectives, it is believed that heuristic techniques may have advantages over direct methods to solve for the beam intensities.

KW - Artificial Intelligence (incl. Robotics)

KW - Business Information Systems

KW - Complexity

KW - Information Storage and Retrieval

KW - Data Storage Representation

KW - Memory Structures

U2 - 10.1007/978-3-7091-7535-4_112

DO - 10.1007/978-3-7091-7535-4_112

M3 - Conference proceeding

SN - 978-3-211-82692-8

SP - 432

EP - 435

BT - Artificial Neural Nets and Genetic Algorithms: Proceedings of the International Conference in Alès, France, 1995

A2 - Pearson, D.W.

A2 - Steele, N. C.

A2 - Albrecht, R. F.

PB - Springer Verlag

CY - Vienna, Austria

ER -