Phase-based computational adaptive optics enables artifact-free super-resolution microscopy
Adaptive optics has revolutionized biological microscopy by improving resolution and signal-to-noise ratio, yet its reliance on complex hardware and phototoxic wavefront sensing limits broader adoption. Here, we introduce ∅CAO, a computational phase-based adaptive optics technique that corrects optical aberrations in three-dimensional fluorescence microscopy without requiring specialized optics or training datasets. By leveraging phase transfer functions in the frequency domain, ∅CAO enables robust post-acquisition correction across diverse imaging modalities, including wide-field and structured illumination microscopy. Our method achieves substantial improvements in image fidelity, supports subregional aberration correction, and maintains performance under noisy conditions. Demonstrated on a range of biological specimens, including Caenorhabditis elegans and plant tissues, ∅CAO offers a scalable and accessible solution for high-resolution biological imaging, facilitating the broad deployment of adaptive optics approaches across the life sciences.
Authors
- Peter M. Carlton (ORCID: https://orcid.org/0000-0002-5320-6024)
- Yosuke Tamada (ORCID: https://orcid.org/0000-0002-4845-4867)
- Atsushi Matsuda (ORCID: https://orcid.org/0000-0003-0510-213X)
- Yamato Matsuo (ORCID: https://orcid.org/0000-0001-5442-8916)
- Takako Koujin
- Carlos Mario Rodriguez-Reza
- Takaharu Yamamoto
Institutions
- National Institute for Basic Biology (JP)
- The Graduate University for Advanced Studies, SOKENDAI (JP)
- Utsunomiya University (JP)
- Kyoto University (JP)
- National Institute of Information and Communications Technology (JP)
Publication Details
- Journal
- Communications Engineering
- Published
- 2026-03-09
- DOI
- https://doi.org/10.1038/s44172-026-00622-7
- Primary Topic
- Advanced Fluorescence Microscopy Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Japan Society for the Promotion of Science
- Core Research for Evolutional Science and Technology