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IMPLEMENTATION AND OPTIMISATION OF MICROWAVE MEDICAL IMAGING BASED ON THE MULTIPLE-FREQUENCY DBIM-TWIST ALGORITHM

机译:基于多频DBIM-TWIST算法的微波医学成像的实现与优化

摘要

The goal of microwave breast imaging is to recover the profile of the dielectric properties of the breast by solving an inverse problem. In this thesis, a novel DBIM algorithm based on the TwIST method is proposed to reconstruct the complex permittivity of 2-D anatomically realistic numerical breast phantoms. A combined optimisation of the algorithm parameters is applied to improve the quality of reconstructions and the robustness of the algorithm. Furthermore, we present new strategies which improve further the performance of the DBIM-TwIST algorithm by refining our previous work on multiple-frequency reconstructions using a single-pole Debye model. Multiple-frequency approaches can combine the stabilizing effects of lower frequencies with enhanced resolution of higher frequencies, thereby overcoming stability and resolution limitations of single-frequency algorithms which tend to be very dependent upon the chosen frequency. And then a novel hybrid frequency approach is proposed to optimise stability and reconstruction accuracy at lower computational cost relative to frequency-hopping techniques. Besides, we propose an innovative two-step reconstruction approach for optimising the initial guess prior to reconstruction. Our approach adds low computational cost to the final breast reconstructions, and improves significantly the reconstruction quality for different breast phantoms. It can then be proposed that an L1 norm regularisation of the TwIST method is based on the Pareto curve, which contributes to de-noising and stabilising the algorithm convergence. At last, we focus on the application of the optimized DBIM-TwIST algorithm to data obtained from an MWI prototype, including direct measured data from MWI experiments, and numerical data from a CAD model emulating the MWI experiments using CST EM software. Based on our new eight-antenna microwave system with a small triangular patch printed monopole, our research demonstrates that the algorithm is able to image cylindrical targets immersed in a background (known) medium despite the model errors due to approximating the real experiment with our 2-D FDTD model. Moreover, a frequency selection method based on correlation analysis is proposed to improve the usage of the frequency information. Finally, we perform image reconstructions using a two-layer medium in order to enhance signal transmission through the imaging domain and at the same time reduce unwanted multi-path signals that do no interact with the interrogated imaging domain.
机译:微波乳房成像的目的是通过解决反问题来恢复乳房介电特性的轮廓。本文提出了一种基于TwIST方法的新型DBIM算法,以重建二维解剖学现实数值乳腺体模的复介电常数。应用算法参数的组合优化来提高重建质量和算法的鲁棒性。此外,我们提出了新的策略,通过改进我们以前使用单极点Debye模型进行多频重构的工作来进一步提高DBIM-TwIST算法的性能。多频方法可以将低频的稳定效果与高频的增强分辨率结合起来,从而克服单频算法的稳定性和分辨率限制,而单频算法的稳定性和分辨率限制往往非常依赖于所选频率。然后提出了一种新颖的混合频率方法,以相对于跳频技术以较低的计算成本来优化稳定性和重构精度。此外,我们提出了一种创新的两步重建方法,用于优化重建之前的初始猜测。我们的方法为最终的乳房重建术增加了较低的计算成本,并显着提高了不同乳房体模的重建质量。然后可以提出,TwIST方法的L1范数正则化基于帕累托曲线,这有助于降低噪声并稳定算法收敛。最后,我们集中讨论优化的DBIM-TwIST算法在从MWI原型获得的数据中的应用,包括MWI实验的直接测量数据和来自使用CST EM软件模拟MWI实验的CAD模型的数值数据。基于我们的新的八天线微波系统,该系统带有一个小的三角形贴片印刷的单极子,我们的研究表明,尽管模型误差由于近似于我们2的真实实验,但该算法仍能够对浸入背景(已知)介质中的圆柱目标成像。 -D FDTD模型。此外,提出了一种基于相关分析的频率选择方法,以提高频率信息的利用率。最后,我们使用两层介质执行图像重建,以增强通过成像域的信号传输,同时减少不与询问的成像域发生交互作用的多余多径信号。

著录项

  • 作者

    Miao Zhenzhuang;

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  • 年度 2018
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  • 原文格式 PDF
  • 正文语种 eng
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