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Simple Signed-Distance Function Depth Calculation Applied to Measurement of the fMRI BOLD Hemodynamic Response Function in Human Visual Cortex

机译:简单符号距离函数深度计算在人类视觉皮层fMRI BOLD血流动力学响应函数测量中的应用

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Functional magnetic resonance imaging (fMRI) often relies on a hemodynamic response function (HRF) elicited by a brief stimulus. At conventional spatial resolutions (> 3 mm), signals in a voxel include contributions from various tissue types and pia vasculature. To better understand these contributions, full characterization of the depth dependence of the HRF is required in gray matter as well as and its apposed white-matter and pial vasculature. We introduce new methods to calculate 3D depth that combines a signed-distance function with an algebraic morphing definition of distance. The new scheme is much simpler than methods that rely upon deformable surface propagation. The method is demonstrated by combining the distance map with high-resolution fMRI (0.9-mm voxels) measurements of the depth-dependent HRF. The depth dependence of the HRF is reliable throughout a broad depth range in gray matter as well as in white-matter and extra-pial compartments apposed to active gray matter. The proposed scheme with high-resolution fMRI can be useful to separate HRFs in the gray matter from undesirable and confounding signals.
机译:功能磁共振成像(fMRI)通常依赖于短暂刺激引起的血液动力学响应功能(HRF)。在常规的空间分辨率(> 3 mm)下,体素中的信号包括来自各种组织类型和pia脉管系统的贡献。为了更好地理解这些贡献,需要对灰质及其与之相关的白质和脉管系统中的HRF的深度依赖性进行全面表征。我们引入了一种新的方法来计算3D深度,该方法将符号距离函数与距离的代数变形定义结合在一起。新方案比依赖可变形表面传播的方法简单得多。通过将距离图与对深度相关的HRF的高分辨率fMRI(0.9毫米体素)测量值结合起来,证明了该方法。 HRF的深度依赖性在灰质以及与活性灰质相对应的白质隔间和外部杂物隔间的广泛深度范围内都是可靠的。所提出的具有高分辨率fMRI的方案可用于将灰质中的HRF与不良信号和混淆信号分开。

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