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Fast brain MRI segmentation based on two-dimensional survival exponential entropy and particle swarm optimization

机译:基于二维存活指数熵和粒子群优化的快速脑MRI分割

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摘要

In this paper, an MRI image segmentation method based on two-dimensional survival exponential entropy (2DSEE) and particle swarm optimization (PSO) is proposed. The 2DSEE technique does not consider only the cumulative distribution of the gray level information but also takes advantage of the spatial information using the 2D-histogram. The problem with this method is its time-consuming computation that is an obstacle in real time applications for instance. We propose to use PSO algorithm, that was proved very efficient for non convex and combinatorial optimization. The experiments on segmentation of MRI images proved that the proposed method can achieve a satisfactory segmentation with a low computation cost.
机译:本文提出了一种基于二维生存指数熵(2DSEE)和粒子群优化(PSO)的MRI图像分割方法。 2DSE技术不考虑灰度信息的累积分布,而且还利用2D直方图利用空间信息。此方法的问题是其耗时的计算,例如实时应用中的障碍。我们建议使用PSO算法,这被证明非常有效地对非凸和组合优化。 MRI图像分割的实验证明,该方法可以通过低计算成本实现令人满意的分割。

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