| --- |
| license: other |
| license_name: modified-apache-2.0-noncommercial |
| license_link: LICENSE |
| extra_gated_heading: "Acknowledge license terms: non-commercial use" |
| extra_gated_button_content: "I agree to the license terms" |
| --- |
| |
| # cellsam |
|
|
| CellSAM is a universal model for cell segmentation. |
| CellSAM achieves state-of-the-art performance on segmentation across a variety |
| of cellular targets (bacteria, tissue, yeast, cell culture, etc.) and |
| imaging modalities (brightfield, fluorescence, phase, multiplexed, etc.). |
|
|
| See the [CellSAM paper][paper] for details! |
|
|
| [paper]: https://www.nature.com/articles/s41592-025-02879-w |
|
|
| ## Model Details |
|
|
| A Vision Transformer (ViT) model building on the detection and segmentation |
| capabilities of the [AnchorDETR][anchordetr-paper] and |
| [Segment Anything (SAM)][sam-paper] models, respectively. |
|
|
| [sam-paper]: https://doi.org/10.1109/ICCV51070.2023.00371 |
| [anchordetr-paper]: https://doi.org/10.1609/aaai.v36i3.20158 |
|
|
| ### Model Description |
|
|
| - **Developed by:** Van Valen Lab |
| - **Funded by:** [Funding details](https://www.nature.com/articles/s41592-025-02879-w#Ack1) |
| - **Model type:** Vision transformer (ViT) |
| - **License:** Modified-apache2.0-noncommercial |
|
|
| ### Model Sources [optional] |
|
|
| - **Repository:** https://github.com/vanvalenlab/cellSAM |
| - **Paper [optional]:** https://www.nature.com/articles/s41592-025-02879-w |
| - **Demo [optional]:** https://vanvalenlab.github.io/cellSAM/auto_examples/index.html |
| |
| ## Uses |
| |
| Cell segmentation in microscope images. |
| |
| ### Direct Use |
| |
| The weights provided in this repository are suitable for cell segmentation |
| across a variety of cellular targets (bacteria, tissue, yeast, cell culture, etc.) |
| and imaging modalities (brightfield, fluorescence, phase, multiplexed, etc.). |
| |
| ### Downstream Use |
| |
| Cellsam is a generalist model designed to perform cell segmentation across all |
| cell types and image modalities. |
| However, it is possible to fine-tune CellSAM for specific applications. |
| See the [methods section of the paper][fine-tuning] for details. |
| |
| [fine-tuning]: https://www.nature.com/articles/s41592-025-02879-w#Sec8 |
| |
| ### Out-of-Scope Use |
| |
| **The model herein is provided subject to license terms prohibiting use for |
| commercial applications.** |
| |
| Inquiries regarding commercial licensing should be directed to the |
| [Caltech Office of Technology Transfer][ottcp]. |
| |
| [ottcp]: https://innovation.caltech.edu/about-ottcp/contact-us#send-us-a-message |
| |
| ## How to Get Started with the Model |
| |
| See the [`cellSAM` tutorial][tutorial] and [example gallery][gallery]. |
| |
| [tutorial]: https://vanvalenlab.github.io/cellSAM/tutorial.html |
| [gallery]: https://vanvalenlab.github.io/cellSAM/auto_examples/index.html |
|
|
| ## Evaluation |
|
|
| [Evaluation protocols][eval] for reproducing the published results can be found |
| in the documentation and source code repository. |
|
|
| [eval]: https://vanvalenlab.github.io/cellSAM/reproducibility.html |
|
|
| ### Testing Data, Factors & Metrics |
|
|
| #### Testing Data |
|
|
| Evaluation data is available via users.deepcell.org. |
|
|
| ## Citation |
|
|
| **BibTeX:** |
|
|
| @article{marks2025cellsam, |
| title={CellSAM: a foundation model for cell segmentation}, |
| author={Marks, Markus and Israel, Uriah and Dilip, Rohit and Li, Qilin and Yu, Changhua and Laubscher, Emily and Iqbal, Ahamed and Pradhan, Elora and Ates, Ada and Abt, Martin and others}, |
| journal={Nature Methods}, |
| volume={22}, |
| number={12}, |
| pages={2585--2593}, |
| year={2025}, |
| publisher={Nature Publishing Group US New York} |
| } |
|
|
| **APA:** |
|
|
| Marks, M., Israel, U., Dilip, R., Li, Q., Yu, C., Laubscher, E., ... & Van Valen, D. (2025). CellSAM: a foundation model for cell segmentation. Nature Methods, 22(12), 2585-2593. |
|
|
