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Source optimization in abstract function spaces for maximizing distinguishability: Applications to the optical tomography inverse problem.

机译:抽象函数空间中的源优化,以最大程度地提高可区分性:在光学层析成像反问题中的应用。

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摘要

The focus of this thesis is to formulate an optimal source problem for the medical imaging technique of optical tomography by maximizing certain distinguishability criteria. We extend the concept of distinguishability in electrical impedance tomography to the frequency-domain diffusion approximation model used in optical tomography.;We consider the dependence of the optimal source on the choice of appropriate function spaces, which can be chosen from certain Sobolev or L p spaces. All of the spaces we consider are Hilbert spaces; we therefore exploit the inner product in several ways. First, we define and use throughout an inner product on the Sobolev space H 1(O) that relates to the model we use for optical tomography. Because of the complex term in our model, the natural sesquilinear form related to the model is not an inner product, and we therefore define and use an operator that relates the H1(O) inner product to the sesquilinear form and therefore the variational formulation. We prove the well-posedness of the variational formulation forward problem of the model using the H1(O) inner product we define.;We also describe in detail an orthogonal decomposition of the space H1(O) in terms of our model, and derive the related inner products and Riesz maps for the subspaces involved in the decomposition as well as their dual spaces, which allows us to define an inner product for the dual of H1(O) as well. We complete this process for two sets of inner products, where the more complicated of the two is included in the Appendices.;To accomplish our goal of maximizing distinguishability, it is necessary to compute the adjoints of the operators described by the model. These computations are not trivial, and we therefore include them for all eight pairs of function spaces. Numerically, we employ the Power Method to compute the optimal sources, which turn out to be the dominant eigenfunctions of the associated operators. We present numerical experiments based on the Power Method to demonstrate the effects of different criteria. A localization measure is also used to determine the optimal source that best discriminates inhomogeneities from a known background. We present in the Appendices an analytical determination of the distinguishability criterion for the special case of an inhomogeneity in the center of a unit disk.;We describe steps toward using these ideas in reconstruction of the optical parameters. We also present some preliminary reconstructions of one of the optical parameters in a certain special case. Numerous questions and problems for further investigation result from the work presented here, and we outline several of these in the final chapter of this thesis.
机译:本文的重点是通过最大化某些可区分性标准,为光学层析成像医学成像技术制定一个最佳光源问题。我们将电阻抗层析成像的可区分性概念扩展到光学层析成像中使用的频域扩散近似模型。;我们考虑了最佳光源对适当功能空间选择的依赖性,可以从某些Sobolev或L p中选择空格。我们考虑的所有空间都是希尔伯特空间;因此,我们以多种方式开发内部产品。首先,我们在Sobolev空间H 1(O)上定义和使用整个内部产品,该内部产品与我们用于光学层析成像的模型有关。由于我们模型中的术语复杂,与模型相关的自然半线性形式不是内部乘积,因此我们定义并使用了将H1(O)内部乘积与半线性形式和变分公式相关联的算子。我们使用定义的H1(O)内积证明了模型的变式正向问题的适定性;我们还根据模型详细描述了空间H1(O)的正交分解,并得出分解涉及的子空间的相关内积和Riesz映射以及它们的对偶空间,这使我们也可以为H1(O)对偶定义一个内积。我们为两组内部产品完成了此过程,其中附录中包括了两组中的更复杂的产品。为了实现最大化可区分性的目标,有必要计算模型描述的算子的伴随。这些计算并非无关紧要,因此我们将所有八对函数空间都包括在内。在数值上,我们采用幂方法来计算最佳源,这是相关算子的主要特征函数。我们提出基于幂方法的数值实验,以证明不同标准的影响。本地化措施还用于确定最佳来源,以最佳方式从已知背景中区分不均匀性。我们在附录中给出了对单位圆盘中心不均匀性的特殊情况的区别性判据的分析确定。;我们描述了在重建光学参数时使用这些思路的步骤。我们还介绍了在某些特殊情况下光学参数之一的一些初步重构。本文提出的工作产生了许多问题,需要进一步研究,我们在本文的最后一章中概述了其中的一些问题。

著录项

  • 作者单位

    Clemson University.;

  • 授予单位 Clemson University.;
  • 学科 Applied Mathematics.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 137 p.
  • 总页数 137
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:37:24

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