An united foundation model for multi-modal optical microscopy

Authors:
  • SCSicheng Chen
    Sicheng Chen
  • CLChenyue Li
    Chenyue Li
  • CWChad K. Wong
    Chad K. Wong
  • QWQinyue Wei
    Qinyue Wei
  • JWJuncheng Wu
    Juncheng Wu
  • YZYuyin Zhou
    Yuyin Zhou
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Abstract
We introduce MicroFoundation, a universal foundation model transforming biomedical optical imaging by unifying semantic understanding with signal restoration. Addressing the fragmentation of current tools, MicroFoundation utilizes a novel architecture and was trained on over 1 million images across seven modalities and vast spatial scales (10 nm to 10 cm). It seamlessly performs diverse tasks, from segmentation to super-resolution, within a single weight set. Benchmarking demonstrates that MicroFoundation significantly outperforms existing specialized and generalist models. By offering a robust, all-in-one solution for image analysis and restoration, MicroFoundation potentially establishes a new standard for the field.