摘要
电阻抗成像(EIT)逆问题具有严重的非线性、病态性和不适定性,导致图像重建不准确.针对该问题,本文提出了一种基于多机制动态搜索(MDS)的电阻抗成像方法.首先,采用Tikhonov正则化方法获得目标区域原始电导率分布矩阵,并将其作为多机制动态搜索算法的输入信息;接着,在搜索空间中对候选解进行随机初始化,根据种群迁移和求偶行为对应的5种选择机制对电导率分布进行动态寻优,再采用目标函数计算每个个体的适应度,将适应度值最小的候选解视为最优解;然后,利用最优解对原始电导率分布进行补偿,获得最优电导率分布;最后,通过仿真和实验验证了该方法的成像效果.结果表明,本文所提方法具有最小的RMSE值,保持在0.15~0.4之间,最大的SSIM值,保持在0.55~0.85之间.与LBP、NR、Tikhonov正规化、TV和GA方法相比,本文所提方法成像质量最好,且在噪声影响下依然具有较好的性能,能够满足准确图像重建的要求.
The inverse problem of electrical impedance tomography(EIT)poses significant challenges due to its seriously non-linear,ill-posed and under-determined nature,which can lead to inaccurate image reconstructions.To address this issue,this paper proposes a novel EIT method based on a multi-mechanism dynamic search.First,the original conductivity distribution matrix of the target region obtained by Tikhonov regularization method is used as the input of the multi-mechanism dynamic search algorithm.Then,the candidate solutions are randomly initialized in the search space,and dynamic optimization of the conductivity distribution is performed based on five selection mechanisms corresponding to population migration and mating behavior.The objective function is then used to calculate the fitness of each individual and the candidate solution with the smallest fitness value is regarded as the optimal solution.Subsequently,the optimal solution is used to compensate the original conductivity distribution,yielding the optimal conductivity distribution.Finally,the imaging quality of this method is verified through simulations and experiments.The results show that the proposed method achieves the lowest root mean square error(RMSE)value,ranging between 0.15 and 0.4,and the highest structural similarity index measure(SSIM)value,varying between 0.55 and 0.85.Compared with other methods,namely LBP,NR,Tikhonov regularization,TV and GA methods,the proposed method demonstrates superior image quality and maintains robust performance under the influence of noise,thereby meeting the requirements for accurate image reconstruction.
作者
施艳艳
崔严
王萌
韩舒悦
刘镇琨
SHI Yanyan;CUI Yan;WANG Meng;HAN Shuyue;LIU Zhenkun(College of Electronic and Electrical Engineering,Henan Normal University,Xinxiang 453007,China;Faculty of Biomedical Engineering,Fourth Military Medical University,Xi’an 710032,China)
出处
《湖南大学学报(自然科学版)》
北大核心
2025年第8期92-102,共11页
Journal of Hunan University:Natural Sciences
基金
国家重点研发计划项目(2021YFC1200104)
河南省自然科学基金杰出青年基金项目(252300421012)
国家自然科学基金资助项目(52277234,52377230)
河南省科技攻关项目(252102221001)。
关键词
电阻抗成像
图像重建
TIKHONOV正则化
电导率分布
多机制动态搜索
electrical impedance tomography(EIT)
image reconstruction
Tikhonov regularization
conductivity distribution
multi-mechanism dynamic search
