In the ever-evolving landscape of biological imaging technology, it is crucial to develop foundation models capable of adapting to various imaging modalities and tackling complex segmentation tasks.
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Acknowledgements
We thank R. Xie and K. Mckeen for insightful discussions. This work was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC, RGPIN-2020-06189 and DGECR-2020-00294), Canadian Institute for Advanced Research (CIFAR) AI Catalyst Grants, and CIFAR AI Chair programs.
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J.M. wrote the manuscript and B.W. edited the original draft and provided funding support. All authors wrote, edited and gave final approval to the manuscript.
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Ma, J., Wang, B. Towards foundation models of biological image segmentation. Nat Methods 20, 953–955 (2023). https://doi.org/10.1038/s41592-023-01885-0
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DOI: https://doi.org/10.1038/s41592-023-01885-0
