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NeuroMorph:一种用于对源自电子显微镜图像堆栈的3D模型进行形态计量分析和可视化的工具集。

NeuroMorph: a toolset for the morphometric analysis and visualization of 3D models derived from electron microscopy image stacks.

作者信息

Jorstad Anne, Nigro Biagio, Cali Corrado, Wawrzyniak Marta, Fua Pascal, Knott Graham

机构信息

Computer Vision Lab, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland,

出版信息

Neuroinformatics. 2015 Jan;13(1):83-92. doi: 10.1007/s12021-014-9242-5.

Abstract

Serialelectron microscopy imaging is crucial for exploring the structure of cells and tissues. The development of block face scanning electron microscopy methods and their ability to capture large image stacks, some with near isotropic voxels, is proving particularly useful for the exploration of brain tissue. This has led to the creation of numerous algorithms and software for segmenting out different features from the image stacks. However, there are few tools available to view these results and make detailed morphometric analyses on all, or part, of these 3D models. We have addressed this issue by constructing a collection of software tools, called NeuroMorph, with which users can view the segmentation results, in conjunction with the original image stack, manipulate these objects in 3D, and make measurements of any region. This approach to collecting morphometric data provides a faster means of analysing the geometry of structures, such as dendritic spines and axonal boutons. This bridges the gap that currently exists between rapid reconstruction techniques, offered by computer vision research, and the need to collect measurements of shape and form from segmented structures that is currently done using manual segmentation methods.

摘要

串行电子显微镜成像对于探索细胞和组织的结构至关重要。块面扫描电子显微镜方法的发展及其捕获大型图像堆栈的能力,其中一些具有近各向同性体素,对于脑组织的探索尤为有用。这导致了许多用于从图像堆栈中分割出不同特征的算法和软件的创建。然而,用于查看这些结果并对这些3D模型的全部或部分进行详细形态计量分析的工具很少。我们通过构建一组名为NeuroMorph的软件工具来解决这个问题,用户可以使用该工具结合原始图像堆栈查看分割结果,在3D中操作这些对象,并对任何区域进行测量。这种收集形态计量数据的方法提供了一种更快的分析结构几何形状的方法,例如树突棘和轴突终扣。这弥合了计算机视觉研究提供的快速重建技术与当前使用手动分割方法从分割结构中收集形状和形态测量值的需求之间目前存在的差距。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a4d/4303738/d1a931a27aaf/12021_2014_9242_Fig1_HTML.jpg

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