Three-dimensional Otsu's method for medical image segmentation based on a simulated annealing particle swarm optimization algorithm
Abstract：Medical image has rich content, various features, and multiple dimensions. Therefore, it is more difficult to segment medical image compared with general image. Aiming at this, a three-dimensional Otsu's method based on an improved particle swarm optimization (PSO) algorithm has been purposed for medical image segmentation. Three-dimensional Otsu's method requires much computation. PSO algorithm can be used to search threshold vectors. Each particle represents a feasible threshold vector. Thus, the optimal threshold can be acquired by the cooperation of particle swarm. Because the PSO algorithm easily sinks into local optimization, so a simulated annealing particle swarm optimization (SAPSO) algorithm has been purposed. The three-dimensional Otsu's method based on SAPSO can rapidly and exactly get the entire optimal results. Simulation experiment results demonstrated that this method could acquire ideal results with less computation.
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Publication Date：2008-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 4380-4384 )