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AI-guided parameter optimization in inverse treatment planning.

Publication ,  Journal Article
Yan, H; Yin, F-F; Guan, H-Q; Kim, JH
Published in: Phys Med Biol
November 7, 2003

An artificial intelligence (AI)-guided inverse planning system was developed to optimize the combination of parameters in the objective function for intensity-modulated radiation therapy (IMRT). In this system, the empirical knowledge of inverse planning was formulated with fuzzy if-then rules, which then guide the parameter modification based on the on-line calculated dose. Three kinds of parameters (weighting factor, dose specification, and dose prescription) were automatically modified using the fuzzy inference system (FIS). The performance of the AI-guided inverse planning system (AIGIPS) was examined using the simulated and clinical examples. Preliminary results indicate that the expected dose distribution was automatically achieved using the AI-guided inverse planning system, with the complicated compromising between different parameters accomplished by the fuzzy inference technique. The AIGIPS provides a highly promising method to replace the current trial-and-error approach.

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Published In

Phys Med Biol

DOI

ISSN

0031-9155

Publication Date

November 7, 2003

Volume

48

Issue

21

Start / End Page

3565 / 3580

Location

England

Related Subject Headings

  • Spinal Neoplasms
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Radiotherapy, Conformal
  • Radiotherapy Planning, Computer-Assisted
  • Radiotherapy Dosage
  • Radiometry
  • Radiation Protection
  • Quality Control
  • Nuclear Medicine & Medical Imaging
 

Citation

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Yan, H., Yin, F.-F., Guan, H.-Q., & Kim, J. H. (2003). AI-guided parameter optimization in inverse treatment planning. Phys Med Biol, 48(21), 3565–3580. https://doi.org/10.1088/0031-9155/48/21/008
Yan, Hui, Fang-Fang Yin, Huai-qun Guan, and Jae Ho Kim. “AI-guided parameter optimization in inverse treatment planning.Phys Med Biol 48, no. 21 (November 7, 2003): 3565–80. https://doi.org/10.1088/0031-9155/48/21/008.
Yan H, Yin F-F, Guan H-Q, Kim JH. AI-guided parameter optimization in inverse treatment planning. Phys Med Biol. 2003 Nov 7;48(21):3565–80.
Yan, Hui, et al. “AI-guided parameter optimization in inverse treatment planning.Phys Med Biol, vol. 48, no. 21, Nov. 2003, pp. 3565–80. Pubmed, doi:10.1088/0031-9155/48/21/008.
Yan H, Yin F-F, Guan H-Q, Kim JH. AI-guided parameter optimization in inverse treatment planning. Phys Med Biol. 2003 Nov 7;48(21):3565–3580.
Journal cover image

Published In

Phys Med Biol

DOI

ISSN

0031-9155

Publication Date

November 7, 2003

Volume

48

Issue

21

Start / End Page

3565 / 3580

Location

England

Related Subject Headings

  • Spinal Neoplasms
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Radiotherapy, Conformal
  • Radiotherapy Planning, Computer-Assisted
  • Radiotherapy Dosage
  • Radiometry
  • Radiation Protection
  • Quality Control
  • Nuclear Medicine & Medical Imaging