Department of Biology, Technion - Israel Institute of Technology, Haifa 32000, Israel.
School of Computing, University of Leeds, Leeds, UK.
STAR Protoc. 2024 Jun 21;5(2):103063. doi: 10.1016/j.xpro.2024.103063. Epub 2024 May 11.
Studying neuronal morphology requires imaging and accurate extraction of tree-like shapes from noisy microscopy data. Here, we present a protocol for automatic reconstruction of branched structures from microscopy images using Neuronalyzer software. We describe the steps for loading neuron images, denoising, segmentation, and tracing. We then detail feature extraction (e.g., branch curvature and junction angles), data analysis, and plotting. The software allows batch processing and statistical comparisons across datasets. Neuronalyzer is scale-free and handles noise and variation across images. For complete details on the use and execution of this protocol, please refer to Yuval et al..
研究神经元形态需要对来自噪声显微镜数据的树状形状进行成像和准确提取。在这里,我们提出了一种使用 Neuronalyzer 软件从显微镜图像自动重建分支结构的方案。我们描述了加载神经元图像、去噪、分割和跟踪的步骤。然后详细介绍了特征提取(例如,分支曲率和连接角度)、数据分析和绘图。该软件支持批处理和跨数据集的统计比较。Neuronalyzer 是无标度的,可以处理图像之间的噪声和变化。有关此方案使用和执行的完整详细信息,请参阅 Yuval 等人的研究。