Automatic Dendritic Length Quantification for High Throughput Screening of Mature Neurons.
Automatic Dendritic Length Quantification for High Throughput Screening of Mature Neurons.
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用于成熟神经元高通量筛选的自动树突长度定量。
DOI：
10.1007/s12021-015-9267-4
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发表时间：
2015
期刊：
影响因子：
3
通讯作者：
Zhou,Jie
中科院分区：
文献类型：
--
作者：
Smafield,Timothy;Pasupuleti,Venkat;Sharma,Kamal;Huganir,RichardL;Ye,Bing;Zhou,Jie
高通量自动荧光成像和筛选对于研究神经元发育、功能和发病机制是重要的。分析以自动方式获得的图像并量化树突特征的自动方法对于使这种筛选高通量是至关重要的。然而，自动和有效的算法和工具，特别是对于具有复杂乔木的成熟哺乳动物神经元的图像，一直缺乏。在这里，我们提出了算法和工具，用于量化树突的长度，是分析神经元网络的增长的基础。我们采用了一个分而治之的框架，解决了神经元的高通量图像的挑战，并使多个自动算法的集成。在这个框架内，我们开发了适应本地属性的算法来检测微弱的分支。我们还开发了一种路径搜索，可以保持曲率变化，以准确地测量树枝的长度与乔木分支和转弯。此外，我们提出了一个集成策略的三个估计算法，以进一步提高整体的功效。我们测试了我们的工具上培养的小鼠海马神经元的图像与树突状标记免疫染色的高通量筛选。结果表明，我们所提出的方法的有效性与以前的方法相比，准确性。该软件已实现为ImageJ插件，可供使用。
High-throughput automated fluorescent imaging and screening are important for studying neuronal development, functions, and pathogenesis. An automatic approach of analyzing images acquired in automated fashion, and quantifying dendritic characteristics is critical for making such screens high-throughput. However, automatic and effective algorithms and tools, especially for the images of mature mammalian neurons with complex arbors, have been lacking. Here, we present algorithms and a tool for quantifying dendritic length that is fundamental for analyzing growth of neuronal network. We employ a divide-and-conquer framework that tackles the challenges of high-throughput images of neurons and enables the integration of multiple automatic algorithms. Within this framework, we developed algorithms that adapt to local properties to detect faint branches. We also developed a path search that can preserve the curvature change to accurately measure dendritic length with arbor branches and turns. In addition, we proposed an ensemble strategy of three estimation algorithms to further improve the overall efficacy. We tested our tool on images for cultured mouse hippocampal neurons immunostained with a dendritic marker for high-throughput screen. Results demonstrate the effectiveness of our proposed method when comparing the accuracy with previous methods. The software has been implemented as an ImageJ plugin and available for use.