Evidence map›Paper›PMID 38404329›Full record

ArticleBiomedical optics express2024

Fast, multicolour optical sectioning over extended fields of view with patterned illumination and machine learning.

Edward N Ward, Rebecca M McClelland, Jacob R Lamb, Roger Rubio-Sánchez, Charles N Christensen, Bismoy Mazumder, Sofia Kapsiani, Luca Mascheroni, Lorenzo Di Michele, Gabriele S Kaminski Schierle and 1 more

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Article in Biomedical optics express, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Edward N WardDepartment of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, CB3 0AS, UK.ORCID https://orcid.org/0000-0002-9078-9716
Rebecca M McClellandDepartment of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, CB3 0AS, UK.ORCID https://orcid.org/0000-0002-9102-8118
Jacob R LambDepartment of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, CB3 0AS, UK.
Roger Rubio-SánchezDepartment of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, CB3 0AS, UK.ORCID https://orcid.org/0000-0001-5574-5809
Charles N ChristensenDepartment of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, CB3 0AS, UK.ORCID https://orcid.org/0000-0002-5355-1063
Bismoy MazumderDepartment of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, CB3 0AS, UK.
Sofia KapsianiDepartment of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, CB3 0AS, UK.
Luca MascheroniDepartment of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, CB3 0AS, UK.
Lorenzo Di MicheleDepartment of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, CB3 0AS, UK.
Gabriele S Kaminski SchierleDepartment of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, CB3 0AS, UK.
Clemens F KaminskiDepartment of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, CB3 0AS, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Structured illumination can reject out-of-focus signal from a sample, enabling high-speed and high-contrast imaging over large areas with widefield detection optics. However, this optical sectioning technique is currently limited by image reconstruction artefacts and poor performance at low signal-to-noise ratios. We combine multicolour interferometric pattern generation with machine learning to achieve high-contrast, real-time reconstruction of image data that is robust to background noise and sample motion. We validate the method

Identifiers

PMID38404329
PMCPMC10890859

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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.