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首页> 外文学位 >Characterization and Comparison of Two Chromophore Determination Techniques: The Modified Beer-Lambert Law (MBLL) and Spatial-Frequency Domain Imaging (SFDI).
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Characterization and Comparison of Two Chromophore Determination Techniques: The Modified Beer-Lambert Law (MBLL) and Spatial-Frequency Domain Imaging (SFDI).

机译：两种生色团测定技术的表征和比较：改良比尔朗伯定律（MBLL）和空频域成像（SFDI）。

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摘要

Optical imaging meets a growing need to non-invasively quantify tissue health in a number of different clinical situations. As optical imaging technology has improved, the ability to quantify biologically-relevant chromophores has grown more accurate but at the cost of increased data acquisition and computation time. For applications such as measurements of functional cerebral activation, in which vascular response occurs on the order of milliseconds to seconds, there is a need for imaging modalities that acquire data quickly and accurately. Spatial-Frequency Domain Imaging (SFDI) is a technique that projects different wavelengths of light in spatially-modulated frequency patterns to quantify absolute optical properties and chromophore concentrations. Since SFDI projects light at different wavelengths and spatially-modulate frequency patterns, it requires several seconds to acquire data. In addition, SFDI requires mathematically rigorous processing techniques to calculate optical properties and chromophore concentrations, which can take several seconds to several hours to complete. A technique called Multi-Spectral Reflectance Imaging (MSRI) relies only on planar reflectance images to quantify changes in chromophore concentration using the Modified Beer-Lambert Law (MBLL), resulting in acquisition and computation times on the order of milliseconds. However, MBLL relies on the assumption of baseline chromophore concentrations in order to deduce absolute chromophore concentrations.;In this thesis I will be investigating a new technique that combines the use of MBLL with SFDI, with the goal of quickly and accurately quantifying chromophore concentrations. I validated the combination technique by first using SFDI to image tissue-simulating phantoms with varying concentrations of absorber, Naphthol Green-B, and constant reduced scattering. Both SFDI and the combination technique were able to calculate the concentration of Naphthol Green-B within 10 percent of the actual concentration after a 100 percent change in Naphthol Green-B concentration. The combination technique took approximately two to three milliseconds on average to calculate the concentration of Naphthol Green-B per iteration of acquisition while SFDI took approximately three to five minutes on average to calculate the concentration of Naphthol Green-B per iteration of acquisition (using a White Monte Carlo processing method). I then analyzed data from an experiment where SFDI was used to measure vascular response in a mouse brain after cortical activation. The combination technique differed from SFDI-calculated chromophore concentrations by 50 percent on average. However, the combination technique took approximately two to three milliseconds on average to calculate chromophore concentrations per iteration of acquisition while SFDI took approximately three to five seconds on average to calculate chromophore concentrations per iteration of acquisition (using the look-up table method). Despite the assumptions made while using the combination technique, the results presented in my thesis show that the combined use of MBLL and SFDI provides a way of quickly and accurately calculating chromophore concentrations for a number of imaging situations.
机译：光学成像满足了在多种不同临床情况下无创地量化组织健康的不断增长的需求。随着光学成像技术的改进，生物相关生色团的定量能力已变得更加准确，但以增加数据获取和计算时间为代价。对于诸如功能性脑部活化的测量的应用，其中血管反应发生在毫秒到秒的数量级，需要一种能够快速而准确地获取数据的成像模式。空频域成像（SFDI）是一种以空间调制的频率模式投射不同波长的光以量化绝对光学特性和生色团浓度的技术。由于SFDI投射不同波长的光并在空间上调制频率模式，因此需要几秒钟来获取数据。此外，SFDI需要数学上严格的处理技术来计算光学性质和生色团浓度，这可能需要几秒钟到几小时才能完成。一种称为多光谱反射成像（MSRI）的技术仅依靠平面反射图像，使用修正比尔朗伯定律（MBLL）来量化发色团浓度的变化，从而导致采集和计算时间约为毫秒。然而，MBLL依赖于基线生色团浓度的假设，以推导出绝对生色团浓度。在本论文中，我将研究一种结合MBLL与SFDI结合使用的新技术，以快速，准确地定量生色团浓度为目标。我首先通过使用SFDI来对具有不同浓度的吸收剂，萘酚绿B以及不断减少的散射的组织模拟体模进行成像，从而验证了组合技术。在萘酚绿B浓度改变100％之后，SFDI和组合技术都能够计算出萘酚绿B的浓度在实际浓度的10％以内。组合技术平均大约需要2到3毫秒才能计算出每次采集的萘酚绿B的浓度，而SFDI平均需要大约3到5分钟才能计算出每次采集的萘酚绿B的浓度（使用白色蒙特卡洛加工方法）。然后，我分析了来自实验的数据，在该实验中，SFDI用于测量皮层激活后小鼠大脑中的血管反应。组合技术与SFDI计算的生色团浓度平均相差50％。但是，组合技术平均大约需要2到3毫秒来计算每次采集的发色团浓度，而SFDI平均大约需要3到5秒来计算每次采集的发色团浓度（使用查找表方法）。尽管在使用组合技术时做出了假设，但我的论文中提出的结果表明，MBLL和SFDI的组合使用为多种成像情况提供了一种快速而准确地计算生色团浓度的方法。

著录项

  • 作者

    Kondru, Clement Joshua.;

  • 作者单位

    University of California, Irvine.;

  • 授予单位 University of California, Irvine.;
  • 学科 Engineering Biomedical.
  • 学位 M.S.
  • 年度 2013
  • 页码 128 p.
  • 总页数 128
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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