Evolutionary Algorithm for Segmentation of Medical Images by Region Rrowing

Ahmad El Allaouil, M. Nasri, M. Merzougui, J. Mirhisse
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引用次数: 5

Abstract

Image segmentation by region growing method is robust fast and very easy to implemented, but it suffers from: the threshold problem, initialization, and sensitivity to noise. Evolutionary algorithms are particular methods for optimizing functions, they have a great ability to find the global optimum of a problem. In this paper, we used evolutionary algorithms to get over the three problems. We have proposed a segmentation method based on region growing and evolutionary algorithms. The proposed approach is validated on four hundred synthetic images and medical. The results show the good performance of this approach.
基于区域生长的医学图像分割进化算法
基于区域增长方法的图像分割具有鲁棒性好、速度快、易于实现等优点,但存在阈值问题、初始化问题和对噪声的敏感性等问题。进化算法是优化函数的一种特殊方法,它具有寻找问题全局最优解的能力。在本文中,我们使用进化算法来解决这三个问题。提出了一种基于区域增长和进化算法的分割方法。该方法在400张合成图像和医学图像上进行了验证。实验结果表明,该方法具有良好的性能。
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