Point spread function decoupling in computational fluorescence microscopy

Ziwei Wang; Wanyu Gu; Shaolei Xu; Yupei Miao; Zewei Cai; Xiang Peng; Xiaoli Liu; Liwei Liu; Qifeng Yu

doi:10.1038/s41377-025-02112-5

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Point spread function decoupling in computational fluorescence microscopy

Original Articles

- Point spread function decoupling in computational fluorescence microscopy
- Light: Science & Applications Vol. 15, Issue 1, Pages: 321-331(2026)
- Affiliations：
  
  1.State Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University, Shenzhen, 518060 Guangdong, China
  2.Shenzhen Key Laboratory of Intelligent Optical Measurement and Detection, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, 518060 Guangdong, China
  3.College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073 Hunan, China
- Author bio：
  
  Zewei Cai (zeweilinc@foxmail.com)
  Xiaoli Liu (lxl@szu.edu.cn)
- Funds：
- DOI：10.1038/s41377-025-02112-5
  CLC：
- Received：14 May 2025，
  
  Revised：2025-09-25，
  
  Accepted：28 October 2025，
  
  Published Online：02 January 2026，
  
  Published：31 January 2026
- Accepted：
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Wang, Z. W. et al. Point spread function decoupling in computational fluorescence microscopy. Light: Science & Applications, 15, 321-331 (2026).
DOI：

Wang, Z. W. et al. Point spread function decoupling in computational fluorescence microscopy. Light: Science & Applications, 15, 321-331 (2026). DOI： 10.1038/s41377-025-02112-5.

摘要

Abstract

Computational fluorescence microscopy constantly breaks through imaging performance through advanced optical modulation technologies; however

conventional theoretical modeling and experimental measurement approaches are challenging to meet the demand for accurate system characterization of diverse modulations. To this end

we propose a point spread function (PSF) decoupling method that is intrinsically compatible with the optimal demodulation in computational microscopic imaging modality. The critical core lies in designing a sample prior-based computational imaging strategy

in which a regular fluorescent sample instead of generally used sub-diffraction limited particles acts as a system modulator to demodulate the system response. PSF consequently can be computationally optimized through the strong support from the modulated sample prior

achieving accurate non-parametric system characterization and thereby avoiding the modeling difficulty and the low signal-to-noise ratio measurement errors of the system specificity. Experimental results across various biological tissues demonstrated and verified that the proposed PSF decoupling method enables excellent volumetric imaging comparable to confocal microscopy and multicolor

large depth-of-field imaging under aperture modulation. It provides a promising mechanism of system characterization and computational demodulation for high-contrast and high-resolution imaging of cellular and subcellular biological structures and life activities.

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