Microglia are immune cells of the central nervous system capable of distinct phenotypic changes and migration in response to injury. These changes most notably include the retraction of fine dendritic structures and adoption of a globular, phagocytic morphology. Due to their characteristic responses, microglia frequently act as histological indicators of injury progression. While algorithms seeking to automate microglia counts and morphological analysis are becoming increasingly popular, few exist that are adequate for use within the retina and manual analysis remains prevalent. To address this, we propose a novel segmentation routine, implemented within FIJI-ImageJ, to perform automated segmentation and cell counting of retinal microglia. We show that our routine could perform cell counts with accuracy similar to manual observers using the I307N Rho model. Tracking cell position relative to retinal vasculature, we observed population migration towards the photoreceptor layer beginning 12 h post light damage. Using feature selection with Chi² and principal component analysis, we resolved cells along a morphological gradient, demonstrating that extracted features were sufficiently descriptive to capture subtle morphological changes within cell populations in I307N Rho and Balb/c TLR2^−/− retinal degeneration models. Taken together, we introduce a novel automated routine capable of efficient image processing and segmentation. Using data retrieved following segmentation, we perform morphological analysis simultaneously on whole populations of cells, rather than individually. Our algorithm was built entirely with open-source software, for use on retinal microglia.

小胶质细胞是中枢神经系统的免疫细胞，能够响应损伤而发生明显的表型变化和迁移。这些变化最显着包括精细树突结构的收缩和球状吞噬形态的采用。由于其特有的反应，小胶质细胞经常作为损伤进展的组织学指标。虽然寻求自动化小胶质细胞计数和形态分析的算法变得越来越流行，但很少有适合在视网膜内使用的算法，手动分析仍然很普遍。为了解决这个问题，我们提出了一种新的分割程序，在 FIJI-ImageJ 中实现，以执行视网膜小胶质细胞的自动分割和细胞计数。我们展示了我们的例程可以执行细胞计数，其准确性类似于使用 I307N 的手动观察者罗模型。跟踪细胞相对于视网膜脉管系统的位置，我们观察到光损伤后 12 小时开始向感光层迁移的群体。使用 Chi ²和主成分分析的特征选择，我们沿形态梯度解析细胞，证明提取的特征具有足够的描述性，可以捕捉 I307N Rho和 Balb/c TLR2中细胞群内的细微形态变化^-/-视网膜变性模型。总之，我们介绍了一种能够进行高效图像处理和分割的新型自动化程序。使用分割后检索到的数据，我们同时对整个细胞群进行形态分析，而不是单独进行。我们的算法完全使用开源软件构建，用于视网膜小胶质细胞。