Publication: Implementation of Automatic Differentiation Tools for Multicriteria IMRT Optimization
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Implementation of Automatic Differentiation Tools for Multicriteria IMRT Optimization

- incollection -
 

Area
Biomedicine

Author(s)
Kyung-Wook Jee , Daniel L. McShan , Benedick A. Fraass

Published in
Automatic Differentiation: Applications, Theory, and Implementations

Editor(s)
H. M. Bücker, G. Corliss, P. Hovland, U. Naumann, B. Norris

Year
2005

Publisher
Springer

Abstract
Automatic differentiation tools (ADOL-C) have been implemented for large-scale NLP optimization problems encountered in an advanced radiotherapy technique called Intensity Modulated Radiation Therapy (IMRT). Since IMRT treatments involve many tissue structures and their associated clinical objectives, the corresponding optimization problems are typically multi-objective. In this study, they are solved by a multi-criteria approach called Lexicographic Ordering. This approach allows clinical objectives to be categorized into several priorities or levels, and optimization is performed sequentially in order of priority while keeping the previously optimized results constrained. As a result, the feasible solution region is gradually reduced as the method progresses. For each level of optimization, the objective function and constraints are constructed interactively by a treatment planner and the corresponding Jacobian is provided by ad tools at a machine-precision level. Results indicate that a high degree of accuracy for Jacobian is essential to produce both feasible and optimal results for clinical IMRT optimization problems.

Cross-References
Bucker2005ADA

AD Tools
ADOL-C

Related Applications
- Intensity Modulated Radiation Therapy

BibTeX
@INCOLLECTION{
         Jee2005IoA,
       author = "Kyung-Wook Jee and Daniel L. McShan and Benedick A. Fraass",
       title = "Implementation of Automatic Differentiation Tools for Multicriteria {IMRT}
         Optimization",
       editor = "H. M. B{\"u}cker and G. Corliss and P. Hovland and U. Naumann and B.
         Norris",
       booktitle = "Automatic Differentiation: {A}pplications, Theory, and Implementations",
       series = "Lecture Notes in Computational Science and Engineering",
       publisher = "Springer",
       year = "2005",
       abstract = "Automatic differentiation tools (ADOL-C) have been implemented for large-scale NLP
         optimization problems encountered in an advanced radiotherapy technique called Intensity Modulated
         Radiation Therapy (IMRT). Since IMRT treatments involve many tissue structures and their associated
         clinical objectives, the corresponding optimization problems are typically multi-objective. In this
         study, they are solved by a multi-criteria approach called Lexicographic Ordering. This approach
         allows clinical objectives to be categorized into several priorities or levels, and optimization is
         performed sequentially in order of priority while keeping the previously optimized results
         constrained. As a result, the feasible solution region is gradually reduced as the method
         progresses. For each level of optimization, the objective function and constraints are constructed
         interactively by a treatment planner and the corresponding Jacobian is provided by AD tools at a
         machine-precision level. Results indicate that a high degree of accuracy for Jacobian is essential
         to produce both feasible and optimal results for clinical IMRT optimization problems.",
       crossref = "Bucker2005ADA",
       ad_area = "Biomedicine",
       ad_tools = "ADOL-C",
       pages = "225--234",
       doi = "10.1007/3-540-28438-9_20"
}


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