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Updated: Aug 17, 2026
Analysis of Microglia and Monocyte-derived Macrophages from the Central Nervous System by Flow Cytometry
Published on: June 22, 2017
μGlia-Flow, an automatic workflow for microglia segmentation and classification
Huangrui Xiong1, Siling Zheng2, Xiuhong Qi3
1School of Information Science and Technology, MoE Key Laboratory of Brain-inspired Intelligent Perception and Cognition, CAS Key Laboratory of Brain Function and Disease, University of Science and Technology of China, Hefei, China; Center for Advanced Interdisciplinary Science and Biomedicine of IHM, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
Background:
Microglia are important immune cells in the central nervous system, playing a key role in various pathological processes. The morphological diversity of microglia is closely linked to the development of brain diseases, yet accurate segmentation and automatic classification of microglia remain challenging.
New Method:
We proposed a workflow, μGlia-Flow, which integrates both segmentation and classification for microglia analysis. The Frangi filtering algorithm was employed for branch segmentation, and an edge-guided attention TransUNet (EGA-Net) was used for soma segmentation. A Vision Transformer (ViT) network was applied to classify different morphologies.
Results:
The Frangi filtering algorithm produces more complete branches with smoother edges and clearer structures. The EGA-Net improves Dice and IoU scores by 4.02 % and 6.75 %, respectively. ViT achieves over 99 % precision in classification. Post-processing reveals decreasing complexity during activation, validating the accuracy of μGlia-Flow.
Comparison With Existing Methods:
μGlia-Flow introduces deep learning, significantly improving segmentation accuracy and addressing the parameter dependency of existing classification methods.
Conclusion:
we present an automatic workflow for segmenting and classifying microglia, providing a powerful tool for different morphology analysis.
