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DeepLabCut Imaging Pipeline
Machine learning-based pose estimation system for tracking zebrafish behavior in custom experimental rigs, enabling high-throughput behavioral analysis.
Source ↗
Python DeepLabCut Computer Vision Pose Estimation
Built a custom ML-based pose estimation system using DeepLabCut to track zebrafish behavior in a purpose-built experimental rig.
Methodology
- DeepLabCut neural network for markerless pose estimation
- Custom training pipeline on labeled video frames
- Automated extraction of behavioral metrics from tracked keypoints
- High-throughput analysis of locomotion patterns and stimulus responses
Impact
- Enabled quantitative behavioral phenotyping previously done by manual observation
- Processed thousands of frames per experiment with consistent accuracy
- Reproducible tracking across multiple experimental sessions