首页> 外文会议>Conference on Optical Tomography and Spectroscopy of Tissue V Jan 26-29, 2003 San Jose, California, USA >Optical Tomographic Brain Imaging with Diffusion and Transport Theory Based Algorithms
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Optical Tomographic Brain Imaging with Diffusion and Transport Theory Based Algorithms

机译:光学层析成像脑成像与扩散和传输理论的基于算法

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There has been considerable discussion concerning the effects of the cerebrospinal fluid on measurements of blood-related parameters in the human brain, and if diffusion-theory-based image reconstruction algorithms can accurately account for the light propagation in the head. All of these studies have been performed either with synthetic data generate from numerical models or from phantom studies. We present here the first comparative study that involves clinical data from optical tomographic measurements. Data obtained from the human forehead during a Valsalva maneuver were input to two different model-based iterative image reconstruction algorithms recently developed in our laboratories. One code is based on the equation of radiative transfer, while the other algorithm uses a diffusion model to describe the light propagation in the head. Both codes use finite-element formulations of the respective theories and were used to obtain three-dimensional volumetric images of oxy, dexoy and total hemoglobin. The reconstructed overall spatial heterogeneity in changes of these parameters is similar using both algorithms. The two codes differ mostly in the amplitude of the observed changes. In general the transport based codes reconstructs changes 10-40% stronger than the diffusion code.
机译:关于脑脊液对人脑中与血液相关的参数的测量,以及基于扩散理论的图像重建算法是否可以准确地解释头部中的光传播,已经进行了大量讨论。所有这些研究都是利用数值模型或幻像研究生成的综合数据进行的。我们在这里提出了第一项比较研究,该研究涉及来自光学层析成像测量的临床数据。在瓦尔萨尔瓦(Valsalva)演习中从人额获得的数据被输入到我们实验室最近开发的两种基于模型的迭代图像重建算法中。一种代码基于辐射传递方程,而另一种算法使用扩散模型来描述光在头部的传播。两种代码均使用各自理论的有限元公式,并用于获得氧,葡聚糖和总血红蛋白的三维体积图像。使用这两种算法,在这些参数的变化中重构的整体空间异质性相似。这两个代码在所观察到的变化幅度上主要不同。通常,基于传输的代码重构的更改比扩散代码要强10-40%。

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