Goethe-University Frankfurt, Goethe-Center for Scientific Computing (G-CSC), 60325 Frankfurt am Main, Germany.
J Biomed Opt. 2012 Jul;17(7):076007. doi: 10.1117/1.JBO.17.7.076007.
SpineLab is a software tool developed for reconstructing neuronal feature skeletons from three-dimensional single- or multi-photon image stacks. These images often suffer from limited resolution and a low signal-to-noise ratio, making the extraction of morphometric information difficult. To overcome this limitation, we have developed a software tool that offers the possibility to create feature skeletons in various modes-automatically as well as with manual interaction. We have named this novel tool SpineLab. In a first step, an investigator adjusts a set of parameters for automatic analysis in an interactive manner, i.e., with online visual feedback, followed by a second step, in which the neuronal feature skeleton can be modified by hand. We validate the ability of SpineLab to reconstruct the entire dendritic tree of identified GFP-expressing neurons and evaluate the accuracy of dendritic spine detection. We report that SpineLab is capable of significantly facilitating the reconstruction of dendrites and spines. Moreover, the automatic approach appears sufficient to detect spine density changes in time-lapse imaging experiments. Taken together, we conclude that SpineLab is an ideal software tool for partially automatic reconstruction of neural cell morphology.
SpineLab 是一款用于从三维单光子或多光子图像堆栈中重建神经元特征骨架的软件工具。这些图像通常存在分辨率有限和信噪比低的问题，使得形态计量信息的提取变得困难。为了克服这一限制，我们开发了一种软件工具，提供了以各种模式创建特征骨架的可能性——自动和手动交互。我们将这个新工具命名为 SpineLab。在第一步中，研究人员以交互方式（即在线视觉反馈）调整一组用于自动分析的参数，然后进入第二步，手动修改神经元特征骨架。我们验证了 SpineLab 重建已识别 GFP 表达神经元的整个树突的能力，并评估了树突棘检测的准确性。我们报告称，SpineLab 能够显著促进树突和棘突的重建。此外，自动方法似乎足以检测延时成像实验中的棘突密度变化。总之，我们得出结论，SpineLab 是用于部分自动重建神经细胞形态的理想软件工具。
