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Hybrid Binary-Real GA Optimization Approach for Breast Microwave Tomography

机译:乳腺X线体层摄影的混合二元-实数遗传算法优化方法

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A microwave tomography imaging system, which uses a hybrid binary-real genetic algorithm (GA) is described in this work. This method utilizes global optimization for solving the inverse scattering problem based on hybrid version of GA, which is the combination of both real and binary-coded GA. This method is principally aimed at breast imaging for the detection of malignant tumors. The proposed technique is based on a time-domain inverse solver, which uses the multi-illumination technique and includes the dispersive and heterogeneous characteristic of the breast tissues. In this algorithm, real-coded GA acts as a regularizer for binary-coded GA and rejects the non-true solutions. The proposed technique is validated using a numerical breast phantom created based on magnetic resonance imaging (MRI) of actual patients. The results are compared with non-hybrid binary and real GAs and the superior efficiency of the proposed method over the methods that solely employ real or binary GA is illustrated.
机译:在这项工作中描述了一种微波层析成像系统,该系统使用混合二进制-实数遗传算法(GA)。此方法基于GA的混合版本,是真实和二进制编码GA的组合,利用全局优化来解决逆散射问题。该方法主要针对乳腺成像以检测恶性肿瘤。所提出的技术基于时域逆解算器,该解算器使用了多重照明技术,并且包含了乳腺组织的分散性和异质性。在此算法中,实数编码GA充当二进制编码GA的正则化器,并拒绝非真解。使用基于实际患者的磁共振成像(MRI)创建的数字乳腺幻像验证了提出的技术。将结果与非混合二进制和实数遗传算法进行比较,说明了该方法相对于仅使用实数或二进制遗传算法的方法具有更高的效率。

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