Automation of 3D reconstruction of neural tissue from large volume of conventional serial section transmission electron micrographs
Automation of 3D reconstruction of neural tissue from large volume of conventional serial section transmission electron micrographs
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DOI：
10.1016/j.jneumeth.2008.09.006
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发表时间：
2009-01-30
影响因子：
3
通讯作者：
Mishchenko, Yuriy
中科院分区：
文献类型：
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作者：
Mishchenko, Yuriy
我们描述了一种方法，从连续切片透射电子显微照片的神经组织重建过程的自动化。这种重建需要在密集的神经元中进行单个神经元过程（轴突和树突）的3D分割。我们首先检测神经元细胞的轮廓，在每个图像中的一叠系列显微照片与多尺度脊检测器。在检测到的边界的短休息内插使用各向异性轮廓完成制定模糊逻辑框架。从相邻部分检测到的配置文件被链接在一起的基础上线索，如形状相似性和图像纹理。由此获得的3D分割由人工操作员在计算机引导的校对过程中进行验证。我们的方法使得神经组织的重建有可能以大约5 μ m（3）/人·h的最终速率进行，这主要取决于校对的速度。到目前为止，我们已经应用这种方法重建了几块神经组织从不同地区的大鼠大脑总计超过1000 μ m（3），并使用这些来评估重建速度，质量，错误率，并存在模糊的位置在neurologysTEM成像数据。(C)2008爱思唯尔有限公司版权所有
We describe an approach for automation of the process of reconstruction of neural tissue from serial section transmission electron micrographs. Such reconstructions require 3D segmentation of individual neuronal processes (axons and dendrites) performed in densely packed neuropil. We first detect neuronal cell profiles in each image in a stack of serial micrographs with multi-scale ridge detector. Short breaks in detected boundaries are interpolated using anisotropic contour completion formulated in fuzzy-logic framework. Detected profiles from adjacent sections are linked together based on cues such as shape similarity and image texture. Thus obtained 3D segmentation is validated by human operators in computer-guided proofreading process. Our approach makes possible reconstructions of neural tissue at final rate of about 5 mu m(3)/man h, as determined primarily by the speed of proofreading. To date we have applied this approach to reconstruct few blocks of neural tissue from different regions of rat brain totaling over 1000 mu m(3), and used these to evaluate reconstruction speed, quality, error rates, and presence of ambiguous locations in neuropil ssTEM imaging data. (C) 2008 Elsevier B.V. All rights reserved