Evidence map›Paper›PMID 39301193›Full record

ArticleAPL photonics2024

Deep-ultraviolet Fourier ptychography (DUV-FP) for label-free biochemical imaging via feature-domain optimization.

Qianhao Zhao, Ruihai Wang, Shuhe Zhang, Tianbo Wang, Pengming Song, Guoan Zheng

Abstract read
In one paragraph

Article in APL photonics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Multiscale aperture synthesis imager.Nature communications · 2025
    Article
  5. Review
  6. Article
  7. Article
  8. Ptychography at all wavelengths.Nature reviews. Methods primers · 2025
    Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Qianhao ZhaoDepartment of Biomedical Engineering, University of Connecticut, Storrs, Connecticut 06269, USA.
Ruihai WangDepartment of Biomedical Engineering, University of Connecticut, Storrs, Connecticut 06269, USA.
Shuhe ZhangUniversity Eye Clinic Maastricht, Maastricht University Medical Center, Maastricht AZ 6202, The Netherlands.
Tianbo WangDepartment of Biomedical Engineering, University of Connecticut, Storrs, Connecticut 06269, USA.
Pengming SongDepartment of Biomedical Engineering, University of Connecticut, Storrs, Connecticut 06269, USA.
Guoan Zheng

Funding

Label-free digital cytopathology using deep-ultraviolet coded ptychography with intrinsic molecular contrastR01EB034744 · NIBIB · UNIVERSITY OF CONNECTICUT STORRS · PI Guoan Zheng · 2023 to 2026
$1.4M
NIBIB NIH HHS R01 EB034744
6 · The paper itself

Abstract

We present deep-ultraviolet Fourier ptychography (DUV-FP) for high-resolution chemical imaging of biological specimens in their native state without exogenous stains. This approach uses a customized 265-nm DUV LED array for angle-varied illumination, leveraging the unique DUV absorption properties of biomolecules at this wavelength region. We implemented a robust feature-domain optimization framework to overcome common challenges in Fourier ptychographic reconstruction, including vignetting, pupil aberrations, stray light problems, intensity variations, and other systematic errors. By using a 0.12 numerical aperture low-resolution objective lens, our DUV-FP prototype can resolve the 345-nm linewidth on a resolution target, demonstrating at least a four-fold resolution gain compared to the captured raw images. Testing on various biospecimens demonstrates that DUV-FP significantly enhances absorption-based chemical contrast and reveals detailed structural and molecular information. To further address the limitations of conventional FP in quantitative phase imaging, we developed a spatially coded DUV-FP system. This platform enables true quantitative phase imaging of biospecimens with DUV light, overcoming the non-uniform phase response inherent in traditional microscopy techniques. The demonstrated advancements in high-resolution, label-free chemical imaging may accelerate developments in digital pathology, potentially enabling rapid, on-site analysis of biopsy samples in clinical settings.

Identifiers

PMID39301193
PMCPMC11409226

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.