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Time reversal optical tomography and decomposition methods for detection and localization of targets in highly scattering turbid media.

机译:时间反转光学层析成像和分解方法,用于在高度散射的混浊介质中检测和定位目标。

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摘要

New near-infrared (NIR) diffuse optical tomography (DOT) approaches were developed to detect, locate, and image small targets embedded in highly scattering turbid media. The first approach, referred to as time reversal optical tomography (TROT), is based on time reversal (TR) imaging and multiple signal classification (MUSIC). The second approach uses decomposition methods of non-negative matrix factorization (NMF) and principal component analysis (PCA) commonly used in blind source separation (BSS) problems, and compare the outcomes with that of optical imaging using independent component analysis (OPTICA). The goal is to develop a safe, affordable, noninvasive imaging modality for detection and characterization of breast tumors in early growth stages when those are more amenable to treatment. The efficacy of the approaches was tested using simulated data, and experiments involving model media and absorptive, scattering, and fluorescent targets, as well as, "realistic human breast model" composed of ex vivo breast tissues with embedded tumors. The experimental arrangements realized continuous wave (CW) multi-source probing of samples and multi-detector acquisition of diffusely transmitted signal in rectangular slab geometry. A data matrix was generated using the perturbation in the transmitted light intensity distribution due to the presence of absorptive or scattering targets. For fluorescent targets the data matrix was generated using the diffusely transmitted fluorescence signal distribution from the targets. The data matrix was analyzed using different approaches to detect and characterize the targets. The salient features of the approaches include ability to: (a) detect small targets; (b) provide three-dimensional location of the targets with high accuracy (~within a millimeter or 2); and (c) assess optical strength of the targets. The approaches are less computation intensive and consequently are faster than other inverse image reconstruction methods that attempt to reconstruct the optical properties of every voxel of the sample volume. The location of a target was estimated to be the weighted center of the optical property of the target. Consequently, the locations of small targets were better specified than those of the extended targets. It was more difficult to retrieve the size and shape of a target. The fluorescent measurements seemed to provide better accuracy than the transillumination measurements. In the case of ex vivo detection of tumors embedded in human breast tissue, measurements using multiple wavelengths provided more robust results, and helped suppress artifacts (false positives) than that from single wavelength measurements. The ability to detect and locate small targets, speedier reconstruction, combined with fluorophore-specific multi-wavelength probing has the potential to make these approaches suitable for breast cancer detection and diagnosis.
机译:开发了新的近红外(NIR)漫射光学层析成像(DOT)方法,以检测,定位和成像嵌入高度散射的混浊介质中的小目标。第一种方法称为时间反转光学层析成像(TROT),它基于时间反转(TR)成像和多信号分类(MUSIC)。第二种方法使用在盲源分离(BSS)问题中常用的非负矩阵分解(NMF)和主成分分析(PCA)分解方法,并将结果与​​使用独立成分分析(OPTICA)的光学成像结果进行比较。目的是开发一种安全,负担得起的非侵入性成像方式,以在乳腺肿瘤较易接受治疗的早期阶段对其进行检测和表征。使用模拟数据以及涉及模型介质和吸收,散射和荧光靶标的实验以及包含离体乳腺组织且内含肿瘤的“现实人乳腺模型”进行了实验,测试了这些方法的有效性。实验装置实现了对样品进行连续波(CW)多源探测,并在矩形平板几何形状中通过多检测器采集了散射信号。由于存在吸收或散射目标,使用透射光强度分布中的扰动生成数据矩阵。对于荧光靶标,使用来自靶标的漫透射荧光信号分布生成数据矩阵。使用不同的方法对数据矩阵进行分析,以检测和表征目标。这些方法的显着特征包括:(a)检测小目标; (b)提供高精度的目标三维定位(〜一毫米或2毫米之内); (c)评估目标的光学强度。该方法的计算强度较小,因此比尝试重建样本体积中每个体素的光学特性的其他逆图像重建方法要快。靶的位置被估计为靶的光学性质的加权中心。因此,小目标的位置要比扩展目标的位置更好。检索目标的大小和形状更加困难。荧光测量似乎提供了比透射照明测量更好的准确性。在离体检测包埋在人乳腺组织中的肿瘤的情况下,与单波长测量相比,使用多个波长的测量可提供更可靠的结果,并有助于抑制伪影(假阳性)。检测和定位小目标的能力,更快的重建能力以及结合荧光团的多波长探测技术,有可能使这些方法适用于乳腺癌的检测和诊断。

著录项

  • 作者

    Wu, Binlin.;

  • 作者单位

    City University of New York.;

  • 授予单位 City University of New York.;
  • 学科 Health Sciences Radiology.;Biophysics General.;Physics Optics.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 332 p.
  • 总页数 332
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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