Evidence map›Paper›PMID 36979887›Full record

ReviewBiomedicines2023

Quantitative Image Processing for Three-Dimensional Episcopic Images of Biological Structures: Current State and Future Directions.

Natalie Aroha Holroyd, Claire Walsh, Lucie Gourmet, Simon Walker-Samuel

Full text readReview
In one paragraph

Review in Biomedicines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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.

Natalie Aroha HolroydCentre for Computational Medicine, University College London, London WC1E 6DD, UK.ORCID 0000-0001-9174-1346
Claire WalshCentre for Computational Medicine, University College London, London WC1E 6DD, UK.
Lucie GourmetCentre for Computational Medicine, University College London, London WC1E 6DD, UK.
Simon Walker-SamuelCentre for Computational Medicine, University College London, London WC1E 6DD, UK.

Funding

Cancer Research UK 28276Cancer Research UK 29458Cancer Research UK C23017/A27935Cancer Research UK C44767/A29458Medical Research Council MR/S007687/1
6 · The paper itself

Abstract

Episcopic imaging using techniques such as High Resolution Episcopic Microscopy (HREM) and its variants, allows biological samples to be visualized in three dimensions over a large field of view. Quantitative analysis of episcopic image data is undertaken using a range of methods. In this systematic review, we look at trends in quantitative analysis of episcopic images and discuss avenues for further research. Papers published between 2011 and 2022 were analyzed for details about quantitative analysis approaches, methods of image annotation and choice of image processing software. It is shown that quantitative processing is becoming more common in episcopic microscopy and that manual annotation is the predominant method of image analysis. Our meta-analysis highlights where tools and methods require further development in this field, and we discuss what this means for the future of quantitative episcopic imaging, as well as how annotation and quantification may be automated and standardized across the field.

Indexed as

annotationepiscopicimagingmicroscopyquantification

Identifiers

PMID36979887
PMCPMC10045950

What Socratic holds

Textfull text, public
LicenceCC BY
measurements read11
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 Socratic graph.