stardist/stardist

Health v2 · maintenance only

Adoption not part of the score

1271 stars · 283 forks observed · 2026-09-29

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

StarDist is a Python library for object detection and instance segmentation in 2D and 3D microscopy images using star-convex shapes, built on deep learning. It is widely used for cell and nuclei segmentation in bioimage analysis.

Use cases

• segment nuclei in fluorescence microscopy images
• detect and segment cells in 3D microscopy volumes
• instance segmentation of cells in histopathology images
• train a deep learning model for object detection in bioimages
• count cells automatically in microscopy data
• segment star-convex shaped objects in 2D images

When to choose

• you need accurate cell or nuclei segmentation in microscopy images
• you work with 2D or 3D bioimage data and want a proven deep learning segmentation method
• objects in your images are roughly star-convex (roundish) shapes
• you want a Python library that integrates with the scientific Python ecosystem

When to avoid

• your objects have highly non-convex, branching shapes better suited to other segmentation methods
• you need general-purpose object detection in natural photos rather than microscopy
• you cannot use GPU-accelerated deep learning frameworks

Facets

library · maturity stable

machine-learning deep-learning image-processing computer-vision bioinformatics computer-vision machine-learning healthcare python cross-platform cell-segmentation nuclei-segmentation bioimage-analysis object-detection microscopy instance-segmentation star-convex

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