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Lecture

Robust Optimization in Radiation Therapy

Related concepts (24)

Convex optimization

Convex optimization is a subfield of mathematical optimization that studies the problem of minimizing convex functions over convex sets (or, equivalently, maximizing concave functions over convex sets). Many classes of convex optimization problems admit polynomial-time algorithms, whereas mathematical optimization is in general NP-hard.

Particle swarm optimization

In computational science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. It solves a problem by having a population of candidate solutions, here dubbed particles, and moving these particles around in the search-space according to simple mathematical formula over the particle's position and velocity.

Linear no-threshold model

The linear no-threshold model (LNT) is a dose-response model used in radiation protection to estimate stochastic health effects such as radiation-induced cancer, genetic mutations and teratogenic effects on the human body due to exposure to ionizing radiation. The model statistically extrapolates effects of radiation from very high doses (where they are observable) into very low doses, where no biological effects may be observed.

Nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC), or nasopharynx cancer, is the most common cancer originating in the nasopharynx, most commonly in the postero-lateral nasopharynx or pharyngeal recess (fossa of Rosenmüller), accounting for 50% of cases. NPC occurs in children and adults. NPC differs significantly from other cancers of the head and neck in its occurrence, causes, clinical behavior, and treatment. It is vastly more common in certain regions of East Asia and Africa than elsewhere, with viral, dietary and genetic factors implicated in its causation.