Evidence map›Paper›PMID 31061769›Full record

ArticleBiomedical optics express2019

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

Li-Hao Yeh, Shwetadwip Chowdhury, Laura Waller

Abstract read
In one paragraph

Article in Biomedical optics express, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Recover Biological Structure from Sparse-View Diffraction Images with Neural Volumetric Prior.Proceedings. IEEE International Conference on Computer Vision · 2025
    Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Super-resolution structured illumination microscopy: past, present and future.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2021
    Article
  11. 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

3 authors.

Li-Hao YehElectrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA.
Shwetadwip ChowdhuryElectrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA.
Laura WallerElectrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA.

Funding

Structured Illumination Computational Microscopy with UV Surface Excitation (MUSE) for Multispectral Super-Resolution HistologyF32GM129966 · NIGMS · UNIVERSITY OF CALIFORNIA BERKELEY · PI CHOWDHURY, SHWETADWIP · 2018 to 2020
$146k
NIGMS NIH HHS F32 GM129966
6 · The paper itself

Abstract

High-content biological microscopy targets high-resolution imaging across large fields-of-view (FOVs). Recent works have demonstrated that computational imaging can provide efficient solutions for high-content microscopy. Here, we use speckle structured illumination microscopy (SIM) as a robust and cost-effective solution for high-content fluorescence microscopy with simultaneous high-content quantitative phase (QP). This multi-modal compatibility is essential for studies requiring cross-correlative biological analysis. Our method uses laterally-translated Scotch tape to generate high-resolution speckle illumination patterns across a large FOV. Custom optimization algorithms then jointly reconstruct the sample's super-resolution fluorescent (incoherent) and QP (coherent) distributions, while digitally correcting for system imperfections such as unknown speckle illumination patterns, system aberrations and pattern translations. Beyond previous linear SIM works, we achieve resolution gains of 4× the objective's diffraction-limited native resolution, resulting in 700 nm fluorescence and 1.2

Identifiers

PMID31061769
PMCPMC6485002

What OpenQuestion holds

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Registered trials

None linked

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.