IMRT beam angle optimization using electromagnetism-like algorithm

The selection of appropriate beam irradiation directions in radiotherapy – beam angle optimization (BAO) problem – is very impor- tant for the quality of the treatment, both for improving tumor irradia- tion and for better organs sparing. However, the BAO problem is still not solved satisfactorily and, most of the time, beam directions continue to be manually selected in clinical practice which requires many trial and error iterations between selecting beam angles and computing fluence patterns until a suitable treatment is achieved. The objective of this pa- per is to introduce a new approach for the resolution of the BAO problem, using an hybrid electromagnetism-like algorithm with descent search to tackle this highly non-convex optimization problem. Electromagnetism- like algorithms are derivative-free optimization methods with the ability to avoid local entrapment. Moreover, the hybrid electromagnetism-like algorithm with descent search has a high ability of producing descent directions. A set of retrospective treated cases of head-and-neck tumors at the Portuguese Institute of Oncology of Coimbra is used to discuss the benefits of the proposed algorithm for the optimization of the BAO problem.Fundação para a Ciência e a Tecnologia (FCT

Dependent coordinates in path integral measure factorization

The transformation of the path integral measure under the reduction procedure in the dynamical systems with a symmetry is considered. The investigation is carried out in the case of the Wiener--type path integrals that are used for description of the diffusion on a smooth compact Riemannian manifold with the given free isometric action of the compact semisimple unimodular Lie group. The transformation of the path integral, which factorizes the path integral measure, is based on the application of the optimal nonlinear filtering equation from the stochastic theory. The integral relation between the kernels of the original and reduced semigroup are obtained.Comment: LaTeX2e, 28 page

A rapid non-iterative proper orthogonal decomposition based outlier detection and correction for PIV data

The present work proposes a novel method of detection and estimation of outliers in particle image velocimetry measurements by the modification of the temporal coefficients associated with a proper orthogonal decomposition of an experimental time series. Using synthetic outliers applied to two sequences of vector fields, the method is benchmarked against stateof-the-art approaches recently proposed to remove the influence of outliers. Compared with these methods, the proposed approach offers an increase in accuracy and robustness for the detection of outliers and comparable accuracy for their estimation