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Related Concept Videos

Overview of Microscopy Techniques01:22

Overview of Microscopy Techniques

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The early pioneers of microscopy opened a window into the invisible world of microorganisms. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes that leveraged nonvisible light, such as fluorescence microscopy that uses an ultraviolet light source and electron microscopy that uses short-wavelength electron beams. These advances significantly improved magnification, image resolution, and contrast. By comparison, the...
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High-speed Particle Image Velocimetry Near Surfaces
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Metasurface-based Fourier ptychographic microscopy.

Cheng Hung Chu1,2, Hao-Pin Chiu1, Cheng Yu3

  • 1Institute of Medical Device and Imaging, National Taiwan University, Taipei 10051, Taiwan.

Nanophotonics (Berlin, Germany)
|December 22, 2025
PubMed
Summary
This summary is machine-generated.

We developed a compact meta-optics microscope using meta-Fourier ptychography (FP) and AI to achieve high-resolution imaging. This portable system overcomes limitations of traditional FP, enabling faster and more accurate quantitative phase imaging.

Keywords:
Fourier ptychographic microscopymetalensquantitative phase imagingresidual convolutional neural network

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Area of Science:

  • Optics and Photonics
  • Computational Imaging
  • Biomedical Engineering

Background:

  • Meta-optics enable miniaturized, high-performance imaging systems.
  • Fourier ptychography (FP) offers high-resolution quantitative phase imaging but traditionally requires bulky optics and mechanical scanning.
  • Existing FP methods face challenges in portability and speed.

Purpose of the Study:

  • To develop a compact and fast Fourier ptychography (FP) microscopy platform.
  • To overcome the limitations of traditional FP systems using meta-optics and artificial intelligence.
  • To demonstrate high-resolution quantitative phase imaging with improved portability and speed.

Main Methods:

  • Integration of a 4-f metalens system for miniaturization.
  • Utilized a programmable thin-film transistor (TFT) panel for angle-diverse illumination without mechanical movement.
  • Employed a residual convolutional neural network (RCNN) for single-shot, high-resolution phase reconstruction from low-resolution inputs.

Main Results:

  • Achieved nearly twofold resolution improvement (7.81 µm to 3.91 µm).
  • Demonstrated accurate quantitative phase recovery with <10% error on phase standards.
  • Showcased reliable dry-mass estimation of H1975 cells with <12% average deviation.

Conclusions:

  • The meta-FP platform offers a fast, compact, and high-performance solution for quantitative phase imaging.
  • Integration of metasurface optics and AI accelerates imaging and enhances resolution.
  • Potential applications include live-cell imaging, microfluidic monitoring, and point-of-care diagnostics.