Computer-vision-based extraction of neural dendrograms
Computer-vision-based extraction of neural dendrograms
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DOI：
10.1016/s0165-0270(99)00120-x
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发表时间：
1999-11-15
影响因子：
3
通讯作者：
Costa, LD
中科院分区：
文献类型：
--
作者：
Cesar, RM;Costa, LD
这项工作介绍了一种新的方法，通过半自动生成树状图来表征神经细胞；树状图是描述神经元树枝结构内在层次性质的数据结构。树状图根据每个树突节段的长度、平均厚度和弯曲能量来描述神经元的分支结构，并允许以直接的方式包括额外的措施。弯曲能量化形状的复杂性，并可用于表征树枝的空间复盖率(弯曲能可替代其他复杂性度量，如分形维)。新的方法是基于根据高曲率点分割细胞的外轮廓，然后对分割的轮廓进行句法分析。半自动方法是稳健的，是对耗时的手动生成树状图的改进。文中给出了几个实验结果，验证了该方法的有效性。本文提出的技术仅限于平面神经元，但可以扩展到3D方法。(C)1999由爱思唯尔科学公司出版。版权所有。
This work introduces a new approach to the characterization of neural cells by means of semi-automated generation of dendrograms; data structures which describe the inherently hierarchical nature of neuronal arborizations. Dendrograms describe the branched structure of neurons in terms of the length, average thickness and bending energy of each of the dendritic segments and allow in a straightforward manner, the inclusion of additional measures. The bending energy quantifies the complexity of the shape and can be used to characterize the spatial coverage of the arborizations (the bending energy is an alternative for other complexity measures such as the fractal dimension). The new approach is based on the partitioning of the cell's outer contour as a function of the high curvature points followed by a syntactical analysis of the segmented contours. The semi-automated method is robust and is an improvement on the time consuming manual generation of the dendrograms. Several experimental results are included in this paper which illustrate and corroborate the effectiveness of the approach. The technique presented in this paper is limited to planar neurons but could be extended to a 3D approach. (C) 1999 Published by Elsevier Science B.V. All rights reserved.