Live neuron morphology automatically reconstructed from multiphoton and confocal Imaging data
Live neuron morphology automatically reconstructed from multiphoton and confocal Imaging data
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DOI：
10.1152/jn.90627.2008
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发表时间：
2008-10-01
影响因子：
2.5
通讯作者：
Saggau, Peter
中科院分区：
文献类型：
--
作者：
Losavio, Bradley E.;Liang, Yong;Saggau, Peter
我们已经开发了一个完全自动化的程序，用于从激光扫描显微镜产生的多个三维图像堆栈中提取树突状形态。通过消除人为干预，我们确保结果客观、快速生成和准确。该软件套件通过减少背景噪音、消除移液器伪影以及对齐多个重叠图像堆栈来考虑典型的实验条件。输出形态适合在房室模拟环境中进行模拟。在这份报告中，我们通过比较其在活神经元和测试样本上的性能与其他全自动和半自动重建工具来验证该程序的实用性。
We have developed a fully automated procedure for extracting dendritic morphology from multiple three-dimensional image stacks produced by laser scanning microscopy. By eliminating human intervention, we ensure that the results are objective, quickly generated, and accurate. The software suite accounts for typical experimental conditions by reducing background noise, removing pipette artifacts, and aligning multiple overlapping image stacks. The output morphology is appropriate for simulation in compartmental simulation environments. In this report, we validate the utility of this procedure by comparing its performance on live neurons and test specimens with other fully and semiautomated reconstruction tools.