Eigenvector-based spatial filtering for reduction of physiological interference in diffuse optical imaging
Eigenvector-based spatial filtering for reduction of physiological interference in diffuse optical imaging
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DOI：
10.1117/1.1852552
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发表时间：
2005-01-01
影响因子：
3.5
通讯作者：
Boas, DA
中科院分区：
文献类型：
--
作者：
Zhang, YH;Brooks, DH;Boas, DA
漫射光学成像是一种有效的无创脑功能成像技术。然而，测量响应由心脏周期、呼吸和血压引起的全身血流动力学波动，这可能模糊或压倒预期的刺激诱发反应。以前在这个问题上的工作采用了时间滤波，从背景像素估计系统效应，或者用预定义的基函数对干扰信号建模，取得了一些成功。然而，微弱的信号仍然会在干扰中丢失，需要其他的补充方法。我们使用测量基线信号的空间行为来识别干扰子空间。然后，我们将该子空间中的信号分量从增产数据中投影出来。在此过程中，我们假设系统干扰成分在空间上比刺激诱发的感兴趣信号更具全局性，具有更高的能量。因此，相应于适当相关矩阵的最大特征值的特征向量构成干涉子空间的基。通过将数据投影到这些特征向量的正交零空间上，我们可以获得更多的局部响应，这体现在改进的噪比和相关系数映射上。(c) 2005年光学仪器工程师学会。
Diffuse optical imaging is an effective technique for noninvasive functional brain imaging. However, the measurements respond to systemic hemodynamic fluctuations caused by the cardiac cycle, respiration, and blood pressure, which may obscure or overwhelm the desired stimulus-evoked response. Previous work on this problem employed temporal filtering, estimation of systemic effects from background pixels, or modeling of interference signals with predefined basis functions, with some success. However, weak signals are still lost in the interference, and other complementary methods are desirable. We use the spatial behavior of measured baseline signals to identify the interference subspaces. We then project signals components in this subspace out of the stimulation data. In doing so, we assume that systemic interference components will be more global spatially, with higher energy, than the stimulus-evoked signals of interest. Thus, the eigenvectors corresponding to the largest eigenvalues of an appropriate correlation matrix form the basis for an interference subspace. By projecting the data onto the orthogonal nullspace of these eigenvectors, we can obtain more localized response, as reflected in improved contrast-to-noise ratio and correlation coefficient maps. (c) 2005 Society of Photo-Optical Instrumentation Engineers.