SAMCell: Generalized label-free biological cell segmentation with segment anything

Using SAMCell, biologists can quickly and automatically obtain cell segmentation results of higher quality than previous methods. Further, these results can be obtained through our custom Graphical User Interface, thus decreasing the human labor required in cell culturing.

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Publication Details

Journal
PLoS ONE
Published
2025-09-08
DOI
https://doi.org/10.1371/journal.pone.0319532
Citations
1
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
1.63
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article

SAMCell: Generalized label-free biological cell segmentation with segment anything

Craig R. Forest, Danfei Xu, Eduardo A. Aponte, Caitlin van Zyl et al.
1 citations
PLoS ONE
Cell Image Analysis Techniques
1.63
article

SAMCell: Generalized label-free biological cell segmentation with segment anything

Craig R. Forest, Danfei Xu, Eduardo A. Aponte, Caitlin van Zyl, Alexandra D. VandeLoo, Nathan J. Malta, Saahil Sanganeriya
article en
1 citations

Abstract

Using SAMCell, biologists can quickly and automatically obtain cell segmentation results of higher quality than previous methods. Further, these results can be obtained through our custom Graphical User Interface, thus decreasing the human labor required in cell culturing.

PLoS ONEVol. 20(9)
Georgia Institute of Technology (US)
Openalex Percentile: Top 12%
Cell Image Analysis Techniques
1.63
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SAMCell: Generalized label-free biological cell segmentation with segment anything — Craig R. Forest, Danfei Xu, et al. · PLoS ONE (2025) | TGRS Research Map | TGRS