Evidence map›Paper›PMID 31772375›Full record

ArticleScientific reports2019

Deconvolution of light sheet microscopy recordings.

Klaus Becker, Saiedeh Saghafi, Marko Pende, Inna Sabdyusheva-Litschauer, Christian M Hahn, Massih Foroughipour, Nina Jährling, Hans-Ulrich Dodt

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Article
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  11. Review
  12. Selective optogenetic control of GNature communications · 2022
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  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Plant-environment microscopy tracks interactions ofProceedings of the National Academy of Sciences of the United States of America · 2021
    Article
  19. Review
  20. 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

8 authors.

Klaus BeckerTU Wien, FKE, Dept. of Bioelectronics, Vienna, Austria. klaus.becker@tuwien.ac.at.ORCID http://orcid.org/0000-0002-2406-0476
Saiedeh SaghafiTU Wien, FKE, Dept. of Bioelectronics, Vienna, Austria.
Marko PendeTU Wien, FKE, Dept. of Bioelectronics, Vienna, Austria.ORCID http://orcid.org/0000-0001-9372-390X
Inna Sabdyusheva-LitschauerTU Wien, FKE, Dept. of Bioelectronics, Vienna, Austria.ORCID http://orcid.org/0000-0001-5989-2267
Christian M HahnCenter for Brain Research, Medical University of Vienna, Vienna, Austria.
Massih ForoughipourTU Wien, FKE, Dept. of Bioelectronics, Vienna, Austria.
Nina JährlingTU Wien, FKE, Dept. of Bioelectronics, Vienna, Austria.ORCID http://orcid.org/0000-0002-7827-9270
Hans-Ulrich DodtTU Wien, FKE, Dept. of Bioelectronics, Vienna, Austria.

Funding

Austrian Science Fund FWF P 23102Austrian Science Fund FWF P 28338
6 · The paper itself

Abstract

We developed a deconvolution software for light sheet microscopy that uses a theoretical point spread function, which we derived from a model of image formation in a light sheet microscope. We show that this approach provides excellent blur reduction and enhancement of fine image details for image stacks recorded with low magnification objectives of relatively high NA and high field numbers as e.g. 2x NA 0.14 FN 22, or 4x NA 0.28 FN 22. For these objectives, which are widely used in light sheet microscopy, sufficiently resolved point spread functions that are suitable for deconvolution are difficult to measure and the results obtained by common deconvolution software developed for confocal microscopy are usually poor. We demonstrate that the deconvolutions computed using our point spread function model are equivalent to those obtained using a measured point spread function for a 10x objective with NA 0.3 and for a 20x objective with NA 0.45.

Identifiers

PMID31772375
PMCPMC6879637

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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.