Index
AI Tools
Machine learning applications, deep learning platforms, and computational pipelines used for microglial morphological analysis, segmentation, and target identification.
Aiforia
Deep Learning / ClassificationCloud-based deep learning platform that allows investigators to train and apply AI models to detect and quantify microglial cells in brain tissue samples.
Key Features
- •Cloud-based infrastructure
- •Custom deep learning model training
- •Cell detection and quantification in tissue
Last reviewed: June 5, 2026
Access Tool →Fiji / ImageJ
Image Processing / SegmentationWidely used open-source software packages featuring powerful machine learning plugins (like Weka) that scientists rely on for 3D stack analysis, segmentation, and quantification of microglia.
Key Features
- •Machine learning plugins (Trainable Weka Segmentation)
- •3D stack analysis
- •Extensive open-source community support
Last reviewed: June 5, 2026
Access Tool →Ilastik
Image Processing / SegmentationAn interactive, open-source machine learning software tool popular for image classification, pixel staging, and microglial cell segmentation without requiring programming experience.
Key Features
- •Interactive pixel and object classification
- •No programming required
- •Random forest-based machine learning
Last reviewed: June 5, 2026
Access Tool →MorphoGlia
Automated Morphological AnalysisCustom machine-learning pipeline for automated morphological analysis of microglia. It allows researchers to rapidly classify shapes, map them spatially in the brain, and track their activation over time with high precision.
Key Features
- •Rapid shape classification
- •Spatial brain mapping
- •Activation tracking over time
Last reviewed: June 5, 2026
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