CellSeg3D: self-supervised 3D cell segmentation for light-sheet microscopy Article Swipe
Cyril Achard
,
Timokleia Kousi
,
M. M. Frey
,
Maxime Vidal
,
Yves Paychère
,
Colin Hofmann
,
Asim Iqbal
,
Sebastien B Hausmann
,
Stéphane Pagès
,
Mackenzie Weygandt Mathis
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.7554/elife.99848.2
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.7554/elife.99848.2
Understanding the complex three-dimensional structure of cells is crucial across many disciplines in biology and especially in neuroscience. Here, we introduce a novel 3D self-supervised learning method designed to address the inherent complexity of quantifying cells in 3D volumes, often in cleared neural tissue. We offer a new 3D mesoSPIM dataset and show that CellSeg3D can match state-of-the-art supervised methods. Our contributions are made accessible through a Python package with full GUI integration in napari.
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- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.7554/elife.99848.2
- OA Status
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- References
- 34
- Related Works
- 10
- OpenAlex ID
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- DOI
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https://doi.org/10.7554/elife.99848.2Digital Object Identifier
- Title
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CellSeg3D: self-supervised 3D cell segmentation for light-sheet microscopyWork title
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preprintOpenAlex work type
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enPrimary language
- Publication year
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2024Year of publication
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2024-12-24Full publication date if available
- Authors
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Cyril Achard, Timokleia Kousi, M. M. Frey, Maxime Vidal, Yves Paychère, Colin Hofmann, Asim Iqbal, Sebastien B Hausmann, Stéphane Pagès, Mackenzie Weygandt MathisList of authors in order
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https://doi.org/10.7554/elife.99848.2Publisher landing page
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://doi.org/10.7554/elife.99848.2Direct OA link when available
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Python (programming language), Clearance, Segmentation, Computer science, Artificial intelligence, Supervised learning, Machine learning, Neuroscience, Artificial neural network, Biology, Medicine, Urology, Operating systemTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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