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Improvements in semiautomated serial section reconstruction and visualization of neural tissue from TEM images

机译:TEM图像对神经组织的半自动连续切片重建和可视化的改进

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Abstract: Our initial system for 3D reconstruction of neural tissue from transmission electron microscope (TEM) images has been improved and expanded in functionality and scope. An automated acquisition system captures images of tissue and controls the movement of a TEM. These images comprise a dataset of roughly one gigabyte. Using these data, software running on a Connection Machine automatically reassembles individual images into a single image of each section. An automated contour extraction and object classification algorithm is used and the objects to be reconstructed are selected by the user. Registration is completely automated, but the result is user verifiable and modifiable. The registration parameters are then used to realign both the contour and raw image data. The contour data are smoothed to average out noise, a surface grid is generated, and the resulting reconstruction is visualized. The image data can also be volume visualized. The result is a completely digital, easy-to-use, quantifiable, and generalizable system for 3D reconstruction from transmission electron microscope serial sections.!8
机译:摘要:我们从透射电子显微镜(TEM)图像中对神经组织进行3D重建的初始系统已得到改进,功能和范围也有所扩展。自动化采集系统捕获组织图像并控制TEM的运动。这些图像包含大约1 GB的数据集。使用这些数据,在连接计算机上运行的软件会自动将单个图像重新组合为每个部分的单个图像。使用自动轮廓提取和对象分类算法,并由用户选择要重建的对象。注册是完全自动化的,但结果是用户可验证和可修改的。配准参数然后用于重新对齐轮廓和原始图像数据。对轮廓数据进行平滑处理以平均出噪声,生成表面网格,并可视化最终的重建结果。图像数据也可以体积可视化。结果是一个完全数字化,易于使用,可量化和通用化的系统,可用于从透射电子显微镜串行部分进行3D重建!8

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