Evidence map›Paper›PMID 35999534›Full record

ArticleBMC biology2022

Extracting multiple surfaces from 3D microscopy images in complex biological tissues with the Zellige software tool.

Céline Trébeau, Jacques Boutet de Monvel, Gizem Altay, Jean-Yves Tinevez, Raphaël Etournay

Abstract read
In one paragraph

Article in BMC biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

5 authors.

Céline TrébeauInstitut Pasteur, Université Paris Cité, Inserm, Institut de l'Audition, F-75012, Paris, France.
Jacques Boutet de MonvelInstitut Pasteur, Université Paris Cité, Inserm, Institut de l'Audition, F-75012, Paris, France.
Gizem AltayInstitut Pasteur, Université Paris Cité, Inserm, Institut de l'Audition, F-75012, Paris, France.
Jean-Yves TinevezInstitut Pasteur, Université Paris Cité, Image Analysis Hub, F-75015, Paris, France. tinevez@pasteur.fr.
Raphaël EtournayInstitut Pasteur, Université Paris Cité, Inserm, Institut de l'Audition, F-75012, Paris, France. raphael.etournay@pasteur.fr.ORCID 0000-0002-2441-9274

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEfficient tools allowing the extraction of 2D surfaces from 3D-microscopy data are essential for studies aiming to decipher the complex cellular choreography through which epithelium morphogenesis takes place during development. Most existing methods allow for the extraction of a single and smooth manifold of sufficiently high signal intensity and contrast, and usually fail when the surface of interest has a rough topography or when its localization is hampered by other surrounding structures of higher contrast. Multiple surface segmentation entails laborious manual annotations of the various surfaces separately.

resultsAs automating this task is critical in studies involving tissue-tissue or tissue-matrix interaction, we developed the Zellige software, which allows the extraction of a non-prescribed number of surfaces of varying inclination, contrast, and texture from a 3D image. The tool requires the adjustment of a small set of control parameters, for which we provide an intuitive interface implemented as a Fiji plugin.

conclusionsAs a proof of principle of the versatility of Zellige, we demonstrate its performance and robustness on synthetic images and on four different types of biological samples, covering a wide range of biological contexts.

Indexed as

AlgorithmsMicroscopyImage Processing, Computer-AssistedImaging, Three-DimensionalSoftware3D imagingFiji pluginImage analysisImage segmentationMorphologySurface extractionTissue imaging

Identifiers

PMID35999534
PMCPMC9397159

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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.