Abstract
We apply the recently proposed superiorization methodology (SM) to the inverse planning problem in radiation therapy. The inverse planning problem is represented here as a constrained minimization problem of the total variation (TV) of the intensity vector over a large system of linear twosided inequalities. The SM can be viewed conceptually as lying between feasibility-seeking for the constraints and full-fledged constrained minimization of the objective function subject to these constraints. It is based on the discovery that many feasibility-seeking algorithms (of the projection methods variety) are perturbation-resilient, and can be proactively steered toward a feasible solution of the constraints with a reduced, thus superiorized, but not necessarily minimal, objective function value.
Original language | English |
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Title of host publication | Contemporary Mathematics |
Publisher | American Mathematical Society |
Pages | 83-92 |
Number of pages | 10 |
DOIs | |
State | Published - 2015 |
Publication series
Name | Contemporary Mathematics |
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Volume | 636 |
ISSN (Print) | 0271-4132 |
ISSN (Electronic) | 1098-3627 |
Bibliographical note
Publisher Copyright:© 2015 R. Davidi, Y. Censor, R. W. Schulte, S. Geneser, L. Xing.
ASJC Scopus subject areas
- General Mathematics