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The role of Cerebral Spinal Fluid in light propagation through the mouse head: Improving fluorescence tomography with Monte Carlo modeling

机译:脑脊髓液在通过小鼠头部的光传播中的作用:通过蒙特卡洛模型改善荧光层析成像

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Optical Neuroimaging is a highly dynamical field of research owing to the combination of many advanced imaging techniques and computational tools that uncovered unexplored paths through the functioning of the brain. Light propagation modelling through such complicated structures has always played a crucial role as the basis for a high resolution and quantitative imaging where even the slightest improvement could lead to significant results. Fluorescence Diffuse Optical Tomography (fDOT), a widely used technique for three dimensional imaging of small animals and tissues, has been proved to be inaccurate for neuroimaging the mouse head without the knowledge of a-priori anatomical information of the subject. Commonly a normalized Born approximation model is used in fDOT reconstruction based on forward photon propagation using Diffusive Equation (DE) which has strong limitations in the optically clear regime. The presence of the Cerebral Spinal Fluid (CSF) instead, a thin optically clear layer surrounding the brain, can be more accurately taken into account using Monte Carlo approaches which nowadays is becoming more usable thanks to parallelized GPU algorithms. In this work we discuss the results of a synthetic experimental comparison, resulting to the increase of the accuracy for the Born approximation by introducing the CSF layer in a realistic mouse head structure with respect to the current model. We point out the importance of such clear layer for complex geometrical models, while for simple slab phantoms neglecting it does not introduce a significant error.
机译:由于许多先进的成像技术和计算工具的结合,光学神经成像技术是一个高度动态的研究领域,它通过大脑功能发现了未探索的路径。通过这样复杂的结构进行光传播建模一直扮演着至关重要的角色,它是高分辨率和定量成像的基础,即使是最细微的改进也可能导致显着结果。荧光扩散光学层析成像(fDOT)是一种广泛用于小型动物和组织的三维成像的技术,已被证明在不了解对象先验解剖信息的情况下无法对小鼠头部进行神经成像。通常,在基于正向光子传播的fDOT重建中,使用扩散方程(DE)使用归一化的Born逼近模型,该模型在光学透明范围内有很强的局限性。相反,使用蒙特卡洛方法可以更准确地考虑到脑脊髓液(CSF)的存在,即围绕大脑的光学透明薄层,由于并行GPU算法,如今这种方法变得越来越有用。在这项工作中,我们讨论了合成实验比较的结果,通过将CSF层引入当前模型的真实鼠标头部结构中,可以提高Born近似的准确性。我们指出了这样的透明层对于复杂的几何模型的重要性,而对于简单的平板模型来说,忽略它并不会带来明显的误差。

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