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基于局部几何和全局结构模型的神经元形态自动重建。

Automated reconstruction of neuronal morphology based on local geometrical and global structural models.

机构信息

Qiushi Academy for Advanced Studies, Zhejiang University, 38 ZheDa Road, Hangzhou 310027, China.

出版信息

Neuroinformatics. 2011 Sep;9(2-3):247-61. doi: 10.1007/s12021-011-9120-3.

Abstract

Digital reconstruction of neurons from microscope images is an important and challenging problem in neuroscience. In this paper, we propose a model-based method to tackle this problem. We first formulate a model structure, then develop an algorithm for computing it by carefully taking into account morphological characteristics of neurons, as well as the image properties under typical imaging protocols. The method has been tested on the data sets used in the DIADEM competition and produced promising results for four out of the five data sets.

摘要

从显微镜图像重建神经元是神经科学中的一个重要且具有挑战性的问题。在本文中,我们提出了一种基于模型的方法来解决这个问题。我们首先构建模型结构,然后通过仔细考虑神经元的形态特征以及典型成像协议下的图像特性,开发出一种用于计算该结构的算法。该方法已经在 DIADEM 竞赛中使用的数据集上进行了测试,对于五个数据集的其中四个,该方法都产生了有前景的结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f39e/3104133/45904f2b445b/12021_2011_9120_Fig1_HTML.jpg

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