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3D Axon Structure Extraction and Analysis in Confocal Fluorescence Microscopy Images

机译:共聚焦荧光显微镜图像中的3D轴突结构提取和分析

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摘要

The morphological properties of axons, such as their branching patterns and oriented structures, are of great interest for biologists in the study of the synaptic connectivity of neurons. In these studies, researchers use triple immunofluorescent confocal microscopy to record morphological changes of neuronal processes. Three-dimensional (3D) microscopy image analysis is then required to extract morphological features of the neuronal structures. In this article, we propose a highly automated 3D centerline extraction tool to assist in this task. For this project, the most difficult part is that some axons are overlapping such that the boundaries distinguishing them are barely visible. Our approach combines a 3D dynamic programming (DP) technique and marker-controlled watershed algorithm to solve this problem. The approach consists of tracking and updating along the navigation directions of multiple axons simultaneously. The experimental results show that the proposed method can rapidly and accurately extract multiple axon centerlines and can handle complicated axon structures such as cross-over sections and overlapping objects.
机译:轴突的形态学特性,例如其分支模式和定向结构,对于生物学家研究神经元的突触连通性非常感兴趣。在这些研究中,研究人员使用三重免疫荧光共聚焦显微镜记录神经元过程的形态变化。然后需要三维(3D)显微镜图像分析以提取神经元结构的形态特征。在本文中,我们提出了一种高度自动化的3D中线提取工具来协助完成此任务。对于此项目,最困难的部分是某些轴突重叠,从而几乎看不到区分它们的边界。我们的方法结合了3D动态编程(DP)技术和标记控制的分水岭算法来解决此问题。该方法包括同时跟踪和更新多个轴突的导航方向。实验结果表明,该方法能够快速,准确地提取出多个轴突中心线,并且能够处理复杂的轴突结构,如交叉截面和重叠物体。

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