Genetic Algorithm Applied to Radiotherapy Treatment Planning

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

doi:10.1007/978-3-7091-7535-4_112

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 proceeding › Conference proceeding › peer-review

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 language	English
Title of host publication	Artificial Neural Nets and Genetic Algorithms: Proceedings of the International Conference in Alès, France, 1995
Editors	D.W. Pearson, N. C. Steele, R. F. Albrecht
Place of Publication	Vienna, Austria
Publisher	Springer Verlag
Pages	432-435
Number of pages	4
ISBN (Print)	978-3-211-82692-8
DOIs	https://doi.org/10.1007/978-3-7091-7535-4_112
Publication status	Published - 1995

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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

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

Access to Document

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

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). 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. et al.
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 proceeding › Conference proceeding › peer-review

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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",

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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.

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KW - Business Information Systems

KW - Complexity

KW - Information Storage and Retrieval

KW - Data Storage Representation

KW - Memory Structures

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EP - 435

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

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A2 - Albrecht, R. F.

PB - Springer Verlag

CY - Vienna, Austria

ER -

Genetic Algorithm Applied to Radiotherapy Treatment Planning

Abstract

Bibliographical note

UN SDGs

Keywords

Access to Document

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Cite this