Ryan G. Lane

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Linear programming is a versatile mathematical tool for optimizing radiation therapy treatment plans. For planning purposes, dose constraint points, possible treatment beams, and an objective function are defined. Dose constraint points are specified in and about the target volume and normal structures with minimum and maximum dose values assigned to each(More)
Two competing methods for assigning intensities to radiation treatment beams were tested. One method was derived from mixed integer programming and the other was based on simulated annealing. The methods faced a common objective and identical constraints. The goal was to maximize the minimum tumor dose while keeping the dose in required fractions of normal(More)
PURPOSE Very Fast Simulated Reannealing is a relatively new (1989) and sophisticated algorithm for simulated annealing applications. It offers the advantages of annealing methods while requiring shorter execution times. The purpose of this investigation was to adapt Very Fast Simulated Reannealing to conformal treatment planning optimization. METHODS AND(More)
A variation of simulated annealing optimization called 'constrained simulated annealing' is used with a simple annealing schedule to optimize beam weights and angles in radiation therapy treatment planning. Constrained simulated annealing is demonstrated using two contrasting objective functions which incorporate both biological response and dose-volume(More)
PURPOSE The efficiency of four fast simulated annealing algorithms for optimizing conformal radiation therapy treatment plans was studied and the resulting plans were compared with each other and to optimized conventional plans. METHODS AND MATERIALS Four algorithms were selected on the basis of their reported successes in solving other minimization(More)
A genetic algorithm for generating beam weights is described. The algorithm improves an objective measure of the dose distribution while respecting dose volume constraints placed on critical structures. The algorithm was used to select beam weights for treatment of abdominal tumors. Weights were selected for up to 36 beams. Dose volume limits were placed on(More)
A method of incorporating dose-volume considerations within the framework of conventional linear programming is presented. This method is suitable for the optimization of beam weights and angles using a conformal treatment philosophy (i.e., tailoring the high-dose region to the target volume only). Dose-volume constraints are introduced using the concept(More)
Recent advances in multicasting over the Internet present new opportunities for improving communication performance in clusters of workstations. The standard IP multicast, however only supports unreliable multicast, which is difficult to use for building high level message passing routines. Thus, reliable multicast primitives must be implemented over the(More)
To efficiently use linear and quadratic programming for treatment planning optimization on a routine basis, automated methods are needed for placing dose constraint points. We have investigated, for linear programming optimization, the minimum number of constraint points needed to achieve an acceptable approximation to the desired (ideal) solution. Seven(More)