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首页> 外文会议>SPIE Conference on Biomedical Applications in Molecular, Structural, and Functional Imaging >Deconvolution of dynamic dual photon microscopy images of cerebralmicrovasculature to assess the hemodynamic status of the brain
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Deconvolution of dynamic dual photon microscopy images of cerebralmicrovasculature to assess the hemodynamic status of the brain

机译：动态双光子显微镜图像脑血管血管分析评估脑血流动力学状态的衰减量

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Assessing the hemodynamic status of the brain and its variations in various situations are required to understand the local cerebral circulatory mechanisms. Dynamic contrast enhanced imaging of cerebral microvasculature provides information that can be used in understanding physiology of cerebral diseases. Bolus tracking is a technique that can be used to extract characteristic parameters that quantify local cerebral blood flow. However, post-processing of the data is needed to segment the FOV and to perform Deconvolution to remove the effects of input bolus profile and the path it travels to reach the imaging window. Finding the arterial input function (AIF) and dealing with the ill-posedness of deconvolution system make this process difficult. We propose using ICA to segment the FOV and to extract a local AIF as well as the venous output function that is required for deconvolution. This also helps to stabilize the system as ICA suppresses noise efficiently. Tikhoniv regularization (with L-curve analysis to find the best regularization parameter) is used to make the system stable and solve the problem. We have acquired dynamic 2PLSM images of a rat brain in two conditions (when the animal is at rest and when it is stimulated) and performed deconvolution. The experimental along with the simulation studies provided promising results that demonstrate the feasibility and importance of performing deconvolution.
机译：评估大脑的血流动力学状态及其各种情况的变化需要了解当地的脑循环机制。动态对比增强的脑微血管成像提供了可用于理解脑病的生理学的信息。推注跟踪是一种可用于提取量化局部脑血流量的特征参数的技术。但是，需要对数据进行后处理来分割FOV并执行解卷积以消除输入推注推注推注的效果，并将其行进到达成像窗口。寻找动脉输入功能（AIF）并处理解压缩系统的不良良好，使这个过程变得困难。我们建议使用ICA进行FOV并提取局部AIF，以及折卷积所需的静脉输出功能。当ICA有效地抑制噪声时，这也有助于稳定系统。 Tikhoniv常规（使用L-Curve分析找到最佳正则化参数）用于使系统稳定并解决问题。我们在两个条件下获得了大鼠大脑的动态2PLSM图像（当动物静置时，当刺激时，刺激）并进行解卷积。该实验以及仿真研究提供了有希望的结果，表明执行折衷的可行性和重要性。

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