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.
|Title of host publication||Contemporary Mathematics|
|Publisher||American Mathematical Society|
|Number of pages||10|
|State||Published - 2015|
Bibliographical notePublisher Copyright:
© 2015 R. Davidi, Y. Censor, R. W. Schulte, S. Geneser, L. Xing.
ASJC Scopus subject areas
- Mathematics (all)