Evidence map›Paper›PMID 34775694›Full record

ArticleJournal of biomedical optics2021

Fast 3D super-resolution imaging using a digital micromirror device and binary holography.

Jialong Chen, Zhiqiang Fu, Bingxu Chen, Shih-Chi Chen

Open access · goldAbstract read
In one paragraph

Article in Journal of biomedical optics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.5field-weighted citation impact, top 14% of its field
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

1 citing paper in PubMed, 7 citations in OpenAlex.

  1. 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

4 authors at 1 institution in 1 country.

Jialong ChenThe Chinese University of Hong Kong, Department of Mechanical and Automation Engineering, Shatin, Hong Kong.
Zhiqiang FuThe Chinese University of Hong Kong, Department of Mechanical and Automation Engineering, Shatin, Hong Kong.
Bingxu ChenThe Chinese University of Hong Kong, Department of Mechanical and Automation Engineering, Shatin, Hong Kong.
Shih-Chi ChenThe Chinese University of Hong Kong, Department of Mechanical and Automation Engineering, Shatin, Hong Kong.
Chinese University of Hong Kong · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

significanceHigh-speed three-dimensional (3D) super-resolution microscopy is a unique tool to investigate various biological phenomena; yet the technology is not broadly adopted due to its high cost and complex system design.

aimWe present a compact, low-cost, and high-speed 3D structured illumination microscopy (SIM) based on a digital micromirror device and binary holography to visualize fast biological events with super-resolution. APPROACH: The 3D SIM uses a digital micromirror device to generate three laser foci with individually controllable positions, phases, and amplitudes via binary holography at the back aperture of objective lens to form optimal 3D structured patterns. Fifteen raw images are sequentially recorded and processed by the 3D SIM algorithm to reconstruct a super-resolved image.

resultsSuper-resolution 3D imaging at a speed of 26.7 frames per second is achieved with a lateral and axial resolution of 155 and 487 nm, which corresponds to a 1.65- and 1.63-times resolution enhancement, respectively, comparing with standard deconvolution microscopy.

conclusionsThe 3D SIM realizes fast super-resolution imaging with optimal 3D structured illumination, which may find important applications in biophotonics.

Indexed as

HolographyImaging, Three-DimensionalAlgorithmsLightingMicroscopybinary holographyfluorescence imagingthree-dimensional structured illumination microscopy

Identifiers

PMID34775694
PMCPMC8590196
OpenAlexW3211387312

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.