Cell segmentation currently involves the use of various bespoke algorithms designed for specific cell types, tissues, staining methods and microscopy technologies. We present a universal algorithm that can segment all kinds of microscopy images and cell types across diverse imaging protocols.
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References
Moen, E. et al. Deep learning for cellular image analysis. Nat. Methods 16, 1233–1246 (2019). A review article that highlights the great potential of deep learning for cell segmentation in microscopy images.
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This is a summary of: Ma, J. et al. The multimodality cell segmentation challenge: toward universal solutions. Nat. Methods https://doi.org/10.1038/s41592-024-02233-6 (2024).
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Creating a universal cell segmentation algorithm. Nat Methods (2024). https://doi.org/10.1038/s41592-024-02254-1
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DOI: https://doi.org/10.1038/s41592-024-02254-1