Evidence map›Paper›PMID 33845806›Full record

ArticleBMC oral health2021

Automated segmentation and description of the internal morphology of human permanent teeth by means of micro-CT.

David Haberthür, Ruslan Hlushchuk, Thomas Gerhard Wolf

Abstract read
In one paragraph

Article in BMC oral health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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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

3 authors.

David HaberthürInstitute of Anatomy, University of Bern, Bern, Switzerland. haberthuer@ana.unibe.ch.ORCID 0000-0003-3388-9187
Ruslan Hlushchuk *Institute of Anatomy, University of Bern, Bern, Switzerland.ORCID 0000-0002-6722-8996
Thomas Gerhard Wolf *Department of Restorative, Preventive and Pediatric Dentistry, School of Dental Medicine, University of Bern, Bern, Switzerland.ORCID 0000-0002-4044-1893

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-resolution micro-computed tomography is a powerful tool to analyze and visualize the internal morphology of human permanent teeth. It is increasingly used for investigation of epidemiological questions to provide the dentist with the necessary information required for successful endodontic treatment. The aim of the present paper was to propose an image processing method to automate parts of the work needed to fully describe the internal morphology of human permanent teeth. One hundred and four human teeth were scanned on a high-resolution micro-CT scanner using an automatic specimen changer. Python code in a Jupyter notebook was used to verify and process the scans, prepare the datasets for description of the internal morphology and to measure the apical region of the tooth. The presented method offers an easy, non-destructive, rapid and efficient approach to scan, check and preview tomographic datasets of a large number of teeth. It is a helpful tool for the detailed description and characterization of the internal morphology of human permanent teeth using automated segmentation by means of micro-CT with full reproducibility and high standardization.

Indexed as

Dental Pulp CavityDentition, PermanentHumansImage Processing, Computer-AssistedReproducibility of ResultsTooth RootX-Ray MicrotomographyAutomated segmentationBiomedical image analysisInternal tooth morphologyMicro-CTPhysiological foramen geometryRoot canal configuration

Identifiers

PMID33845806
PMCPMC8040229

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Registered trials

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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.