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**Delaunay-Watershed-3D** is an algorithm designed to reconstruct a sparse representation of the geometry of tissues and cell nuclei from instance segmentations, in 3D. It accomplishes this by building multimaterial meshes from segmentation masks. These multimaterial meshes are perfectly suited for **storage, geometrical analysis, sharing** and **visualisation of data**. We provide high level APIs to extract geometrical features from the meshes, as well as visualisation tools based on [polyscope](https://polyscope.run) and [napari](https://napari.org).
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Delaunay-Watershed was created by Sacha Ichbiah during his PhD in [Turlier Lab](https://www.turlierlab.com), and is maintained by Sacha Ichbiah, Matthieu Perez and Hervé Turlier. For support, please open an issue.
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A preprint of the method will be published soon. If you use our library in your work please cite the paper.
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If you use this library in your work please cite the [paper](https://doi.org/10.1101/2023.04.12.536641).
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Introductory notebooks with precise use case are provided.
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Introductory notebooks on two examples (cells in an aggregate and nuclei) are provided.
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The algorithm takes as input segmentation masks and return multimaterial triangle meshes (3D).
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This method is used as a backend for [foambryo](https://github.com/VirtualEmbryo/foambryo), our 3D tension inference library.
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This method is used as a backend for [foambryo](https://github.com/VirtualEmbryo/foambryo), our 3D tension and pressure inference library.
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### Example
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### Quick start example
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Load an instance segmentation, reconstruct its multimaterial mesh, and extract its geometry:
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Load an instance segmentation, construct its multimaterial mesh, and extract geometrical features of cells:
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