标题： 通过三维光片显微镜图像对小鼠脑血管系统的拓扑分析 显示英文标题

标题： Topological Analysis of Mouse Brain Vasculature via 3D Light-sheet Microscopy Images

摘要： 血管网络在理解大脑功能方面起着至关重要的作用。 大脑的完整性和功能、神经元活动和可塑性，这些对于学习至关重要，它们的局部环境，特别是血管网络，会积极地进行调节。 随着高分辨率三维光片显微成像技术以及组织处理技术的最新发展，现在可以获取并检查小鼠的大规模脑血管。 然而，为了建立功能研究的结构基础，我们需要先进的图像分析和结构建模方法。 现有工作使用几何特征，如厚度、迂回程度等。 然而，几何特征无法完全捕捉诸如分支的丰富性、连通性等结构特征。 在本文中，我们通过拓扑视角研究脑血管的形态。 我们基于拓扑数据分析理论提取拓扑特征。 在不同脑解剖结构之间以及正常人群和肥胖人群之间比较这些稳健且多尺度的拓扑结构特征，为它们在研究神经系统疾病中的未来应用提供了启示。 显示英文摘要

摘要： Vascular networks play a crucial role in understanding brain functionalities. Brain integrity and function, neuronal activity and plasticity, which are crucial for learning, are actively modulated by their local environments, specifically vascular networks. With recent developments in high-resolution 3D light-sheet microscopy imaging together with tissue processing techniques, it becomes feasible to obtain and examine large-scale brain vasculature in mice. To establish a structural foundation for functional study, however, we need advanced image analysis and structural modeling methods. Existing works use geometric features such as thickness, tortuosity, etc. However, geometric features cannot fully capture structural characteristics such as the richness of branches, connectivity, etc. In this paper, we study the morphology of brain vasculature through a topological lens. We extract topological features based on the theory of topological data analysis. Comparing of these robust and multi-scale topological structural features across different brain anatomical structures and between normal and obese populations sheds light on their promising future in studying neurological diseases.