Automated reconstruction of neuronal morphology: An overview

被引:114
作者
Donohue, Duncan E.
Ascoli, Giorgio A. [1 ]
机构
[1] George Mason Univ, Ctr Neural Informat Struct & Plast, Fairfax, VA 22030 USA
关键词
Automated reconstruction; Neuronal morphology; Neuron tracing; Image analysis; Vectorization; FLUORESCENCE MICROSCOPY IMAGES; DENDRITIC MORPHOLOGY; CONFOCAL IMAGES; ALGORITHMS; STACKS; QUANTIFICATION; MORPHOMETRY; VALIDATION; EXTRACTION; MODELDB;
D O I
10.1016/j.brainresrev.2010.11.003
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Digital reconstruction of neuronal morphology is a powerful technique for investigating the nervous system. This process consists of tracing the axonal and dendritic arbors of neurons imaged by optical microscopy into a geometrical format suitable for quantitative analysis and computational modeling. Algorithmic automation of neuronal tracing promises to increase the speed, accuracy, and reproducibility of morphological reconstructions. Together with recent breakthroughs in cellular imaging and accelerating progress in optical microscopy, automated reconstruction of neuronal morphology will play a central role in the development of high throughput screening and the acquisition of connectomic data. Yet, despite continuous advances in image processing algorithms, to date manual tracing remains the overwhelming choice for digitizing neuronal morphology. We summarize the issues involved in automated reconstruction, overview the available techniques, and provide a realistic assessment of future perspectives. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:94 / 102
页数:9
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