Evidence map›Paper›PMID 30561432›Full record

ArticleScientific data2018

A preclinical micro-computed tomography database including 3D whole body organ segmentations.

Stefanie Rosenhain, Zuzanna A Magnuska, Grace G Yamoah, Wa'el Al Rawashdeh, Fabian Kiessling, Felix Gremse

Abstract readDataset
In one paragraph

Article in Scientific data, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

  1. Applications of artificial intelligence in nuclear medicine.Zeitschrift fur medizinische Physik · 2026
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  3. Head of the Syrian Hamster (Animals : an open access journal from MDPI · 2026
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  8. Postmortem CT: Applications in Clinical and Forensic Medicine.Radiographics : a review publication of the Radiological Society of North America, Inc · 2025
    Review
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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

6 authors.

Stefanie RosenhainInstitute for Experimental Molecular Imaging, University Hospital Aachen, Forckenbeckstr. 55, 52074 Aachen, Germany.
Zuzanna A MagnuskaInstitute for Experimental Molecular Imaging, University Hospital Aachen, Forckenbeckstr. 55, 52074 Aachen, Germany.
Grace G YamoahInstitute for Experimental Molecular Imaging, University Hospital Aachen, Forckenbeckstr. 55, 52074 Aachen, Germany.
Wa'el Al RawashdehMiltenyi Biotec GmbH, Friedrich-Ebert-Str. 68, 51429 Bergisch Gladbach, Germany.
Fabian KiesslingInstitute for Experimental Molecular Imaging, University Hospital Aachen, Forckenbeckstr. 55, 52074 Aachen, Germany.ORCID 0000-0002-7341-0399
Felix GremseInstitute for Experimental Molecular Imaging, University Hospital Aachen, Forckenbeckstr. 55, 52074 Aachen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The gold-standard of preclinical micro-computed tomography (μCT) data processing is still manual delineation of complete organs or regions by specialists. However, this method is time-consuming, error-prone, has limited reproducibility, and therefore is not suitable for large-scale data analysis. Unfortunately, robust and accurate automated whole body segmentation algorithms are still missing. In this publication, we introduce a database containing 225 murine 3D whole body μCT scans along with manual organ segmentation of most important organs including heart, liver, lung, trachea, spleen, kidneys, stomach, intestine, bladder, thigh muscle, bone, as well as subcutaneous tumors. The database includes native and contrast-enhanced, regarding spleen and liver, μCT data. All scans along with organ segmentation are freely accessible at the online repository Figshare. We encourage researchers to reuse the provided data to evaluate and improve methods and algorithms for accurate automated organ segmentation which may reduce manual segmentation effort, increase reproducibility, and even reduce the number of required laboratory animals by reducing a source of variability and having access to a reliable reference group.

Indexed as

Databases, FactualX-Ray MicrotomographyAnimalsImage Processing, Computer-AssistedMiceWhole Body Imaging

Identifiers

PMID30561432
PMCPMC6298256

What OpenQuestion holds

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LicenceCC BY
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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.