ArticleScientific reports2024
Svetlana a supervised segmentation classifier for Napari.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- MyoFuse is a fully AI-based workflow for automated quantification of skeletal muscle cell fusion in vitro.Scientific reports · 2026Article
- OoCount: a machine-learning-based approach to mouse ovarian follicle counting and classification†.Biology of reproduction · 2025Article
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Authors and funding
3 authors.
Funding
Abstract
We present Svetlana (SuperVised sEgmenTation cLAssifier for NapAri), an open-source Napari plugin dedicated to the manual or automatic classification of segmentation results. A few recent software tools have made it possible to automatically segment complex 2D and 3D objects such as cells in biology with unrivaled performance. However, the subsequent analysis of the results is oftentimes inaccessible to non-specialists. The Svetlana plugin aims at going one step further, by allowing end-users to label the segmented objects and to pick, train and run arbitrary neural network classifiers. The resulting network can then be used for the quantitative analysis of biophysical phenoma. We showcase its performance through challenging problems in 2D and 3D and provide a comprehensive discussion on its strengths and limits.
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Registered trials
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