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Automated fluence map optimization based on fuzzy inference systems
Publication . Dias, Joana; Rocha, Humberto; Ventura, Tiago; BC Ferreira; Lopes, Maria do Carmo
The planning of an intensity modulated radiation therapy treatment requires the optimization of the fluence intensities. The fluence map optimization (FMO) is many times based on a nonlinear continuous programming problem, being necessary for the planner to define a priori weights and/or lower bounds that are iteratively changed within a trial-and-error procedure until an acceptable plan is reached. In this work, the authors describe an alternative approach for FMO that releases the human planner from trial-and-error procedures, contributing for the automation of the planning process.
Noncoplanar beam angle optimization in IMRT treatment planning using pattern search methods
Publication . Rocha, Humberto; Dias, Joana M; Costa Ferreira, Brigida; Lopes, Maria C
Radiation therapy is used to treat localized cancers, aiming to deliver a dose of radiation to the tumor volume to sterilize all cancer cells while minimizing the collateral effects on the surrounding healthy organs and tissues. The planning of radiation therapy treatments requires decisions regarding the angles used for radiation incidence, the fluence intensities and, if multileaf collimators are used, the definition of the leaf sequencing. The beam angle optimization problem consists in finding the optimal number and incidence directions of the irradiation beams. The selection of appropriate radiation incidence directions is important for the quality of the treatment. However, the possibility of improving the quality of treatment plans by an optimized selection of the beam incidences is seldom done in the clinical practice. Adding the possibility for noncoplanar incidences is even more rarely used. Nevertheless, the advantage of noncoplanar beams is well known. The optimization of noncoplanar beam incidences may further allow the reduction of the number of beams needed to reach a clinically acceptable plan. In this paper we present the benefits of using pattern search methods for the optimization of the highly non-convex noncoplanar beam angle optimization problem.

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Funding agency

Fundação para a Ciência e a Tecnologia

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COMPETE

Funding Award Number

PTDC/EIA-CCO/121450/2010

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