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Learning-based segmentation using star-convex object representations, with workflows for microscopy images. Suitability depends on object shapes, training data and image dimensions.
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Learning-based segmentation using star-convex object representations, with workflows for microscopy images. Suitability depends on object shapes, training data and image dimensions.
Información cotejada con una fuente oficial; no es un ensayo experimental directo. Fuente · Última revisión: 14/09/2026, 18:31:56 UTC
Use this citation format when referencing StarDist in scientific publications and benchmark papers.
@software{stardist_2026,
title = {{StarDist}},
author = {{StarDist contributors}},
year = {2026},
url = {https://github.com/stardist/stardist},
note = {Indexed on aibioatlas - AI for Biology and Drug Discovery}
}Live scientific citations queried from Europe PMC and PubMed for StarDist.
Missing values mean the catalog has no recorded information. They do not mean a feature is absent.
Project documentation; editorial evaluation plan · Compare these alternative analysis tools on the same images; no cross-tool interoperability is asserted.
StarDist Scientific Architecture · Credit: StarDist contributors · Open original ↗
Research and editorial use Source & attribution ↗ License ↗
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