2015/01/01 by Ran Davidi, Yair Censor, R. Schulte +2 · 2 citations
Medicine · Physics and Astronomy · Engineering · #Medical Imaging Techniques and Applications #Advanced Radiotherapy Techniques #Advanced X-ray and CT Imaging
paper · doi:10.1090/conm/636/12729
openalex publication_date 2015/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/06/11
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 two-sided 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.