Project
CellGalaxy - Multiscale Exploration of Biomedical Image Embeddings
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CellGalaxy is a scalable visual analytics system for exploring and interpreting deep image embeddings from multiplex biomedical imaging datasets.
CellGalaxy is a visual analytics system for exploring and interpreting deep image embeddings from large-scale biomedical imaging datasets. It combines scalable embedding visualization, semantic zooming, and AI-assisted explanations to help researchers connect learned representations with tissue and cellular structures.
## Features
- Scalable Visualization**: Explore millions of biomedical image embeddings.
- Semantic Zooming**: Navigate across tissue, region, and cellular scales.
- Linked Views**: Connect embedding space with spatial tissue context.
- Interactive Filtering**: Identify and compare biologically relevant patterns.
- AI-Assisted Explanations**: Interpret learned representations with integrated AI agents.
## Links
- GitHub: [github.com/nyu-vis-krueger-group/CellGalaxy](https://github.com/nyu-vis-krueger-group/CellGalaxy)