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Related Concept Videos

Imaging Biological Samples with Optical Microscopy01:18

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Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
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Confocal microscopy is an advanced microscopic technique. The prime advantage of the confocal microscope over other microscopy techniques is its ability to block the out-of-focus light from the illuminated samples using pinholes. It is widely used with fluorescence optics to obtain high-resolution, sharp contrast images. Unlike optical microscopes, confocal microscopes use a focused beam of light laser to scan the entire sample surface at different z-planes. These microscopes are, therefore,...
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Related Experiment Video

Updated: Jan 15, 2026

Lensfree On-chip Tomographic Microscopy Employing Multi-angle Illumination and Pixel Super-resolution
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LensPlus: a high space-bandwidth optical imaging technique.

Neha Goswami1,2, Mark A Anastasio1,3

  • 1Department of Bioengineering, University of Illinois Urbana-Champaign, Illinois, 61801, USA.

Biomedical Optics Express
|January 14, 2026
PubMed
Summary
This summary is machine-generated.

LensPlus, a deep learning framework, enhances the space-bandwidth product (SBP) in quantitative phase imaging (QPI) by recovering lost high-frequency details. This enables simultaneous high-resolution and large field-of-view imaging without hardware changes.

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Area of Science:

  • Optical imaging
  • Computational imaging
  • Deep learning applications

Background:

  • Space-bandwidth product (SBP) limits simultaneous high-resolution and large field-of-view imaging.
  • High-NA objectives offer resolution but limited coverage; low-NA objectives offer coverage but limited resolution.

Purpose of the Study:

  • Introduce LensPlus, a deep learning framework to enhance SBP in quantitative phase imaging (QPI).
  • Achieve high-resolution and large field-of-view imaging without hardware modifications.

Main Methods:

  • Developed a deep learning framework (LensPlus) trained on paired low-NA and high-NA QPI datasets.
  • LensPlus recovers high-frequency features from low-NA images to emulate high-NA performance.
  • Employed a non-generative model to ensure quantitative fidelity and minimize image hallucinations.

Main Results:

  • LensPlus transformed 10x/0.3 NA images to quality comparable to 40x/0.95 NA.
  • Achieved a 2D-SBP improvement of approximately 3.5x.
  • Demonstrated quantitative fidelity through spectral analysis.

Conclusions:

  • LensPlus effectively increases SBP by bridging the resolution gap while preserving field of view.
  • The framework is broadly applicable to various lens-based imaging modalities.
  • Enables practical wide-field, high-resolution imaging for demanding applications.