Fig. 2

Schematic showing the machine learning pipeline and the different microglia measurements extracted from the analysis. A Schematic visualising the microglia labelling using machine learning. In panel A (left), the red label indicates microglia, the blue label indicates blood vessels, and the yellow label indicates the background of the images. The red label was used as inclusion criteria, and the other two labels were used as exclusion criteria for microglia labelling.. The microglia circled in yellow in panel A (right) was used as the microglia model for panel B. B Schematic depicting a visual representation of the measurements extracted from our machine learning analysis and manual analysis. Machine learning metrics included 3D metrics like cell volume, convex hull volume, and cell solidity (cell volume divided by convex hull volume), and 2D metrics like cell perimeter, convex hull perimeter, cell convexity, cell circularity, minor axis length, major axis length, and axis ratio. Manual analysis only allowed for 2D metrics to be analysed such as cell area, perimeter, convex hull area, convex hull perimeter, cell solidity (cell area divided by convex hull area) cell convexity, cell circularity, minor axis length, major axis length, and axis ratio. The schematic in B was designed in CorelDRAW X6