利用遗传算法精确重建电阻抗断层成像图像

Mahdi Abbasi, M. Zareie, A. Amer, Mohammad Hossein Khosravi
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引用次数: 0

摘要

求解电阻抗层析成像逆问题的方法之一是D-bar法,它是一种直接且无重复的求解方法。在这个方法中,使用了一个称为a的特定运算符。在D-bar积分方程中,积分范围被认为是一个以坐标原点为圆心,半径为R的圆,这个积分只有在$k$≤| $R$ |时才是非零值。在这个方程中,所使用的半径R对重建图像的分辨率是有效的。在本文中,我们使用遗传算法获得最佳半径,以产生均方误差最小的优化图像。因此,通过增加离散节点,将所考虑的模型划分为三个阶段,并对其实施遗传算法进行评估。结果表明,每一步的最优半径增大,均方误差减小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Accurate Reconstruction of Electrical Impedance Tomography Images Using Genetic Algorithm
One of the methods to solve the inverse problem of electrical impedance tomography is D-bar method, which is the direct and no repetition solution. In this method, a specific operator called a is used. In the D-bar integral equation, range of integration is considered a circle with the center of origin of coordinates and radius R. This integration is non-zero value only for $k$ ≤ | $R$ |. In this equation, the used radius R, is effective in the resolution of the reconstructed image. In this paper, we used genetic algorithm to obtain the best radius to produce the optimized image with minimum mean square error. Therefore, the considered model was meshed up to three stages, by increasing the discretization nodes and implemented genetic algorithm was evaluated on it. We showed that the optimum radius was increased and mean square error was decreased at each step.
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