MRI brain tumor recognition using Modified Shuffled Frog Leaping Algorithm

Anis Ladgham, A. Sakly, A. Mtibaa
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引用次数: 9

Abstract

This paper presents a novel optimal algorithm for MRI brain tumor recognition. To do this, we use the newly developed meta-heuristic MSFLA (Modified Shuffled Frog Leaping Algorithm). Otherwise, a suitable choice of the fitness function ensures faster time of research with greater chance of convergence to the optimal value. The calculation of the used fitness function is linked to the image. The image must be scanned to calculate this function. For this, this function assists to quickly discover the adequate area modeling the tumor. Computer simulation results illustrate the effectiveness of the developed algorithm.
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基于改进的洗牌青蛙跳跃算法的MRI脑肿瘤识别
提出了一种新的MRI脑肿瘤识别优化算法。为了做到这一点,我们使用了新开发的元启发式MSFLA (Modified shuffledfrog跳跃算法)。否则,选择合适的适应度函数可以保证更快的研究时间和更大的收敛到最优值的机会。所使用的适应度函数的计算与图像相关联。必须扫描图像来计算这个函数。为此,该功能有助于快速发现适当的肿瘤建模区域。计算机仿真结果表明了该算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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