Cited by 63Cell Image Analysis TechniquesAdvanced Fluorescence Microscopy TechniquesImage Processing Techniques and Applications

Automated analysis of images for molecular quantification in immunohistochemistry

Open access
Guirado, Ramon, Carceller, Héctor, Castillo-Gómez, Esther, Castrén, Eero, Nacher, Juan·2018·Heliyon

Abstract

The quantification of the expression of different molecules is a key question in both basic and applied sciences. While protein quantification through molecular techniques leads to the loss of spatial information and resolution, immunohistochemistry is usually associated with time-consuming image analysis and human bias. In addition, the scarce automatic software analysis is often proprietary and expensive and relies on a fixed threshold binarization. Here we describe and share a set of macros ready for automated fluorescence analysis of large batches of fixed tissue samples using FIJI/ImageJ. The quantification of the molecules of interest are based on an automatic threshold analysis of immunofluorescence images to automatically identify the top brightest structures of each image. These macros measure several parameters commonly quantified in basic neuroscience research, such as neuropil density and fluorescence intensity of synaptic puncta, perisomatic innervation and col-localization of different molecules and analysis of the neurochemical phenotype of neuronal subpopulations. In addition, these same macro functions can be easily modified to improve similar analysis of fluorescent probes in human biopsies for diagnostic purposes based on the expression patterns of several molecules.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.heliyon.2018.e00669

Cites

33 of 33 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Guirado, R., Carceller, H., Castillo-Gómez, E., Castrén, E., & Nacher, J.
Affiliations
  • Universitat de València (ES)
  • Universitat Jaume I (ES)
Venue
Heliyon
Publisher
Elsevier BV
Published
2018-06
Volume
4
Issue
6
Pages
e00669
ISSN
2405-8440 (ISSN-L)
OpenAlex
W2810608517
Cited by
63
References
33
Citations by year
2026: 7 · 2025: 4 · 2024: 8 · 2023: 4 · 2022: 11 · 2021: 11 · 2020: 8 · 2019: 9 · 2018: 1
FWCI
3.79
Type
journal article
Language
en
Open access
Locations
  • Heliyon (publishedVersion, cc-by-nc-nd)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • Repositori UJI (Universitat Jaume I) (publishedVersion, cc-by-nc-nd)
  • LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, cc-by-nc-nd)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Työväentutkimus Vuosikirja (submittedVersion)
Funders
  • Spanish Ministry of Science (#BES, 2007–15757)
  • ERC Advanced grant (#322742-iPlasticity)
  • Academy of Finland (#257486)
  • Spanish Ministry of Economy and Competitiveness (SAF2015-68436-R)
  • Juan de la Cierva program (IJCI-2016-27758)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Cell Image Analysis Techniques
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Advanced Fluorescence Microscopy Techniques
  • Physical Sciences › Engineering › Media Technology › Image Processing Techniques and Applications
Keywords
automated image analysis, immunohistochemistry, immunofluorescence, automatic thresholding, colocalization, neuronal subpopulations, neurochemical phenotype, fluorescence intensity measurement

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review