Evidence map›Paper›PMID 33708381›Full record

ArticleF1000Research2020

Effective image visualization for publications - a workflow using open access tools and concepts.

Christopher Schmied, Helena Klara Jambor

Abstract read
In one paragraph

Article in F1000Research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
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  9. Article
  10. Ten simple rules for designing graphical abstracts.PLoS computational biology · 2024
    Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
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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

2 authors.

Christopher Schmied *Leibniz-Forschungsinstitut für Molekulare Pharmakologie im Forschungsverbund Berlin e.V. (FMP), Berlin, Germany.ORCID 0000-0003-2058-1124
Helena Klara Jambor *Mildred-Scheel Early Career Center, Medical Faculty, Technische Universität Dresden, Dresden, Germany.ORCID 0000-0003-3397-1842

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Today, 25% of figures in biomedical publications contain images of various types, e.g. photos, light or electron microscopy images, x-rays, or even sketches or drawings. Despite being widely used, published images may be ineffective or illegible since details are not visible, information is missing or they have been inappropriately processed. The vast majority of such imperfect images can be attributed to the lack of experience of the authors as undergraduate and graduate curricula lack courses on image acquisition, ethical processing, and visualization.  Here we present a step-by-step image processing workflow for effective and ethical image presentation. The workflow is aimed to allow novice users with little or no prior experience in image processing to implement the essential steps towards publishing images. The workflow is based on the open source software Fiji, but its principles can be applied with other software packages. All image processing steps discussed here, and complementary suggestions for image presentation, are shown in an accessible "cheat sheet"-style format, enabling wide distribution, use, and adoption to more specific needs.

Indexed as

Access to InformationImage Processing, Computer-AssistedFijiSoftwareWorkflowBeginner's workflowFIJIGood principles of figure designImage analysisImage processingImage Publicationopen sourceVisualization

Identifiers

PMID33708381
PMCPMC7931257.2

What OpenQuestion holds

Textmetadata
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.