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Computational structured illumination for high-content fluorescence and phase microscopy.

Li-Hao Yeh1, Shwetadwip Chowdhury1, Laura Waller1

  • 1Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA.

Biomedical Optics Express
|May 8, 2019
PubMed
Summary
This summary is machine-generated.

Speckle structured illumination microscopy (SIM) offers cost-effective, high-content imaging. This method achieves 4x resolution for fluorescence and quantitative phase imaging, enabling detailed biological analysis.

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Area of Science:

  • Biomedical imaging
  • Optical microscopy
  • Computational imaging

Background:

  • High-content biological microscopy requires high-resolution imaging over large fields-of-view (FOVs).
  • Computational imaging offers efficient solutions for high-content microscopy.
  • Multi-modal imaging is crucial for correlative biological analysis.

Purpose of the Study:

  • To present a robust and cost-effective speckle structured illumination microscopy (SIM) method.
  • To enable simultaneous high-content fluorescence and quantitative phase (QP) imaging.
  • To achieve super-resolution across large FOVs with digital correction of system imperfections.

Main Methods:

  • Utilized laterally-translated Scotch tape to generate high-resolution speckle illumination patterns.
  • Employed custom optimization algorithms for joint reconstruction of fluorescence and QP distributions.
  • Digitally corrected for unknown speckle patterns, aberrations, and translations.

Main Results:

  • Achieved 4x resolution enhancement over diffraction-limited native resolution.
  • Obtained 700 nm resolution for fluorescence and 1.2 μm for QP imaging.
  • Demonstrated a large field-of-view with a space-bandwidth product (SBP) of 60 megapixels.

Conclusions:

  • Speckle SIM provides a cost-effective solution for high-content multi-modal microscopy.
  • The method enables simultaneous super-resolution fluorescence and quantitative phase imaging.
  • This technique supports advanced correlative biological analysis with high spatial resolution.