Evidence map›Paper›PMID 34513850›Full record

ArticleFrontiers in cell and developmental biology2021

A New Pipeline to Automatically Segment and Semi-Automatically Measure Bone Length on 3D Models Obtained by Computed Tomography.

Santiago Beltran Diaz, Chee Ho H'ng, Xinli Qu, Michael Doube, John Tan Nguyen, Michael de Veer, Olga Panagiotopoulou, Alberto Rosello-Diez

Open access · goldAbstract read
In one paragraph

Article in Frontiers in cell and developmental biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 38% of its field
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

4 citing papers in PubMed, 4 citations in OpenAlex.

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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

8 authors at 3 institutions in 2 countries.

Santiago Beltran DiazAustralian Regenerative Medicine Institute, Monash University, Clayton, VIC, Australia.
Chee Ho H'ngAustralian Regenerative Medicine Institute, Monash University, Clayton, VIC, Australia.
Xinli QuAustralian Regenerative Medicine Institute, Monash University, Clayton, VIC, Australia.
Michael DoubeDepartment of Infectious Diseases and Public Health, City University of Hong Kong, Kowloon, Hong Kong, SAR China.
John Tan NguyenAustralian Regenerative Medicine Institute, Monash University, Clayton, VIC, Australia.
Michael de VeerMonash Biomedical Imaging, Monash University, Clayton, VIC, Australia.
Olga PanagiotopoulouDepartment of Anatomy and Developmental Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia.
Alberto Rosello-DiezAustralian Regenerative Medicine Institute, Monash University, Clayton, VIC, Australia.
Monash University · AUAustralian Regenerative Medicine Institute · AUCity University of Hong Kong · HK

Funding

Wellcome Trust
6 · The paper itself

Abstract

The characterization of developmental phenotypes often relies on the accurate linear measurement of structures that are small and require laborious preparation. This is tedious and prone to errors, especially when repeated for the multiple replicates that are required for statistical analysis, or when multiple distinct structures have to be analyzed. To address this issue, we have developed a pipeline for characterization of long-bone length using X-ray microtomography (XMT) scans. The pipeline involves semi-automated algorithms for automatic thresholding and fast interactive isolation and 3D-model generation of the main limb bones, using either the open-source ImageJ plugin BoneJ or the commercial Mimics Innovation Suite package. The tests showed the appropriate combination of scanning conditions and analysis parameters yields fast and comparable length results, highly correlated with the measurements obtained

Indexed as

bone growth and developmentBoneJlimb evolutionmicro-CT (computed tomography)MIMICSskeletal phenotype analysis

Identifiers

PMID34513850
PMCPMC8427701
OpenAlexW3198221841

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.