A genetic algorithm with neural network fitness function evaluation for IMRT beam angle optimization
Author
Abstract
Suggested Citation
DOI: 10.1007/s10100-013-0289-4
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Lim, Gino J. & Cao, Wenhua, 2012. "A two-phase method for selecting IMRT treatment beam angles: Branch-and-Prune and local neighborhood search," European Journal of Operational Research, Elsevier, vol. 217(3), pages 609-618.
- Shanker, M. & Hu, M. Y. & Hung, M. S., 1996. "Effect of data standardization on neural network training," Omega, Elsevier, vol. 24(4), pages 385-397, August.
- J. Deasy & E. Lee & T. Bortfeld & M. Langer & K. Zakarian & J. Alaly & Y. Zhang & H. Liu & R. Mohan & R. Ahuja & A. Pollack & J. Purdy & R. Rardin, 2006. "A collaboratory for radiation therapy treatment planning optimization research," Annals of Operations Research, Springer, vol. 148(1), pages 55-63, November.
- H. Rocha & J. Dias & B. Ferreira & M. Lopes, 2013. "Selection of intensity modulated radiation therapy treatment beam directions using radial basis functions within a pattern search methods framework," Journal of Global Optimization, Springer, vol. 57(4), pages 1065-1089, December.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Guillermo Cabrera-Guerrero & Andrew J. Mason & Andrea Raith & Matthias Ehrgott, 2018. "Pareto local search algorithms for the multi-objective beam angle optimisation problem," Journal of Heuristics, Springer, vol. 24(2), pages 205-238, April.
- Gerhard Weber & Jacek Blazewicz & Marion Rauner & Metin Türkay, 2014. "Recent advances in computational biology, bioinformatics, medicine, and healthcare by modern OR," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 22(3), pages 427-430, September.
- Aydin Azizi, 2017. "Introducing a Novel Hybrid Artificial Intelligence Algorithm to Optimize Network of Industrial Applications in Modern Manufacturing," Complexity, Hindawi, vol. 2017, pages 1-18, June.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- James R. Coakley & Carol E. Brown, 2000. "Artificial neural networks in accounting and finance: modeling issues," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 9(2), pages 119-144, June.
- Matteo Picozzi & Antonio Giovanni Iaccarino, 2021. "Forecasting the Preparatory Phase of Induced Earthquakes by Recurrent Neural Network," Forecasting, MDPI, Open Access Journal, vol. 3(1), pages 1-20, January.
- Zhang, Guoqiang & Y. Hu, Michael & Eddy Patuwo, B. & C. Indro, Daniel, 1999. "Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis," European Journal of Operational Research, Elsevier, vol. 116(1), pages 16-32, July.
- Lim, Gino J. & Bard, Jonathan F., 2016. "Benders decomposition and an IP-based heuristic for selecting IMRT treatment beam anglesAuthor-Name: Lin, Sifeng," European Journal of Operational Research, Elsevier, vol. 251(3), pages 715-726.
- Zaghian, Maryam & Lim, Gino J. & Khabazian, Azin, 2018. "A chance-constrained programming framework to handle uncertainties in radiation therapy treatment planning," European Journal of Operational Research, Elsevier, vol. 266(2), pages 736-745.
- Zhang, Gioqinang & Hu, Michael Y., 1998. "Neural network forecasting of the British Pound/US Dollar exchange rate," Omega, Elsevier, vol. 26(4), pages 495-506, August.
- H. Rocha & J. Dias & B. Ferreira & M. Lopes, 2013. "Selection of intensity modulated radiation therapy treatment beam directions using radial basis functions within a pattern search methods framework," Journal of Global Optimization, Springer, vol. 57(4), pages 1065-1089, December.
- Sauré, Antoine & Patrick, Jonathan & Tyldesley, Scott & Puterman, Martin L., 2012. "Dynamic multi-appointment patient scheduling for radiation therapy," European Journal of Operational Research, Elsevier, vol. 223(2), pages 573-584.
- Shigeyuki Hamori & Takahiro Kume, 2018.
"Artificial Intelligence And Economic Growth,"
Advances in Decision Sciences, Asia University, Taiwan, vol. 22(1), pages 256-278, December.
- Shigeyuki Hamori & Takahiro Kume, 2018. "Artificial Intelligence And Economic Growth," International Association of Decision Sciences, Asia University, Taiwan, vol. 22(1), pages 256-278, December.
- Yasin Gocgun, 2018. "Simulation-based approximate policy iteration for dynamic patient scheduling for radiation therapy," Health Care Management Science, Springer, vol. 21(3), pages 317-325, September.
- Alessandro Agnetis & Alberto Coppi & Matteo Corsini & Gabriella Dellino & Carlo Meloni & Marco Pranzo, 2014. "Operations management e sanità: un sistema di supporto alle decisioni per la programmazione della chirurgia elettiva," MECOSAN. Menagement e economia sanitaria, FrancoAngeli Editore, vol. 2014(90), pages 55-69.
- Guillermo Cabrera-Guerrero & Andrew J. Mason & Andrea Raith & Matthias Ehrgott, 2018. "Pareto local search algorithms for the multi-objective beam angle optimisation problem," Journal of Heuristics, Springer, vol. 24(2), pages 205-238, April.
- Gino Lim & Laleh Kardar & Wenhua Cao, 2014. "A hybrid framework for optimizing beam angles in radiation therapy planning," Annals of Operations Research, Springer, vol. 217(1), pages 357-383, June.
- Marc C. Robini & Feng Yang & Yuemin Zhu, 2020. "A stochastic approach to full inverse treatment planning for charged-particle therapy," Journal of Global Optimization, Springer, vol. 77(4), pages 853-893, August.
- Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
- Dunbar, Michelle & O’Brien, Ricky & Froyland, Gary, 2020. "Optimising lung imaging for cancer radiation therapy," European Journal of Operational Research, Elsevier, vol. 282(3), pages 1038-1052.
More about this item
Keywords
Genetic algorithms; Radiotherapy; IMRT; Surrogate model; Neural networks;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:cejnor:v:22:y:2014:i:3:p:431-455. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Springer Nature Abstracting and Indexing). General contact details of provider: http://www.springer.com .
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.