MaSkel and napari-MaSkel: fast morphological skeleton feature extraction from segmentation masks

Authors

Wittmann, S., Pysch, D., Uderhardt, S., Blumenthal, D. B., Moeller, A.

Abstract

Summary: Existing workflows for extracting morphological features from network-like biomedical structures often require several heterogeneous tools, which can limit integration and reproducibility. We present MaSkel and napari-MaSkel, open-source Python tools that provide GUI- and CLI-based workflows for 2D and 3D skeletonization and graph-based feature extraction, using a substantially accelerated implementation of the widely used Lee94 thinning algorithm. Availability and Implementation: MaSkel and napari-MaSkel are open-source Python packages available under the MIT license on PyPI and GitHub: https://github.com/bionetslab/maskel/, https://github.com/bionetslab/napari-maskel/. Documentation: https://bionetslab.github.io/maskel/, https://bionetslab.github.io/napari-maskel/. Benchmarking and validation: https://github.com/bionetslab/maskel-evaluations.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 22 Sep 2026.

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