janelia-cellmap/dacapo
A framework for easy application of established machine learning techniques on large, multi-dimensional images.
This tool helps life scientists and researchers efficiently process extremely large, multi-dimensional biological images, such as those from electron microscopy, to automatically identify and segment structures like cells or organelles. You provide your raw image data and define what you want to find, and it outputs precise segmentations that highlight these structures. It's designed for biologists, microscopists, and anyone working with high-resolution image analysis in scientific research.
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Use this if you need to apply established machine learning methods to automatically segment features within very large, complex 3D or 4D biological image datasets.
Not ideal if you are working with standard 2D images, small datasets, or do not require advanced machine learning for image segmentation.
Stars
60
Forks
10
Language
Python
License
BSD-3-Clause
Category
Last pushed
Sep 15, 2025
Commits (30d)
0
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