AI-guided parameter optimization in inverse treatment planning.
Journal Article (Journal Article)
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.
- Yan, H; Yin, F-F; Guan, H-Q; Kim, JH
- November 7, 2003
Volume / Issue
- 48 / 21
Start / End Page
- 3565 - 3580
International Standard Serial Number (ISSN)
Digital Object Identifier (DOI)