Evidence map›Paper›PMID 33543383›Full record

ArticleClinical oral investigations2021

Application of image processing techniques to aid in the detection of vertical root fractures in digital periapical radiography.

Lucas Exposto Soares, Deborah Queiroz Freitas, Kaique Leite de Lima, Lorena Rosa Silva, Fernanda Paula Yamamoto-Silva, Marcelo Andrade da Costa Vieira

Open access · greenAbstract read
PubMed Publisher
In one paragraph

Article in Clinical oral investigations, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-weighted citation impact, top 30% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. 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

6 authors at 3 institutions in 2 countries.

Lucas Exposto SoaresDepartment of Electrical and Computer Engineering, São Carlos School of Engineering, University of São Paulo, Av. Trab. São Carlense, 400, São Carlos, São Paulo, 13566-590, Brazil.ORCID http://orcid.org/0000-0001-8772-6899
Deborah Queiroz FreitasDepartment of Oral Diagnosis, Division of Oral Radiology, Piracicaba Dental School, University of Campinas, Av. Limeira, 901, Piracicaba, São Paulo, 13414-903, Brazil.ORCID http://orcid.org/0000-0002-1425-5966
Kaique Leite de LimaDepartment of Stomatological Sciences, School of Dentistry, Federal University of Goiás, Av. Universitária s/n, Goiânia, Goiás, 74605-220, Brazil.ORCID http://orcid.org/0000-0003-2996-1334
Lorena Rosa SilvaDepartment of Stomatological Sciences, School of Dentistry, Federal University of Goiás, Av. Universitária s/n, Goiânia, Goiás, 74605-220, Brazil.ORCID http://orcid.org/0000-0003-4037-6400
Fernanda Paula Yamamoto-SilvaDepartment of Stomatological Sciences, School of Dentistry, Federal University of Goiás, Av. Universitária s/n, Goiânia, Goiás, 74605-220, Brazil.ORCID http://orcid.org/0000-0002-2918-7708
Marcelo Andrade da Costa VieiraDepartment of Electrical and Computer Engineering, São Carlos School of Engineering, University of São Paulo, Av. Trab. São Carlense, 400, São Carlos, São Paulo, 13566-590, Brazil. mvieira@sc.usp.br.ORCID http://orcid.org/0000-0002-6038-7740
Universidade Federal de Goiás · BRUniversidade de São Paulo · BRUniversidade Estadual de Campinas (UNICAMP) · BR

Funding

Conselho Nacional de Desenvolvimento Científico e Tecnológico (BR) 457536/2014-4Instituto Federal de Educação, Ciência e Tecnologia de São Paulo 23305.008073.2018-58
6 · The paper itself

Abstract

objectivesTo present an image processing framework to improve the detection of vertical root fractures (VRFs) in digital periapical radiography. MATERIALS AND

methodsThirty endodontically treated human teeth (15 of them fractured with a metal post inserted into them, and 15 for the control) were enclosed in a dry mandible and radiographed individually. The proposed framework was applied to the raw data, as a preprocessing step, and was composed of four stages: geometric adjustment and negative, denoising, adaptive contrast enhancement, and gamma correction. The contrast-to-noise ratio (CNR) and sharpness of the image's VRF region were used for the objective evaluation of the method. In addition, five examiners evaluated the original and enhanced images, using a 5-point scale to assess confidence.

resultsThe objective results showed that the proposed framework increased the CNR of the VRF region by 173% compared to the standard preprocessing method provided by the detector's manufacturer. The results found by the human observers indicated that the area under the curve (AUC) and sensitivity of the diagnosis of VRF significantly increased by 4% and 17% (p ≤ 0.05), respectively, when the examiners evaluated the image with the proposed method concomitantly with the image available in the commercial software. However, the specificity was reduced.

conclusionsThe proposed image processing framework can be used as an additional tool to that provided by the manufacturer to increase the sensitivity and AUC of the diagnosis of VRF. CLINICAL RELEVANCE: The proposed method can be easily used in clinical practice to aid VRF detection, since it does not incur high computational costs and does not increase the radiation dose applied to the patient.

Indexed as

Tooth FracturesTooth, NonvitalCone-Beam Computed TomographyHumansRadiography, Dental, DigitalTooth RootDigital periapical radiographyImage processingRadiographic image enhancementVertical root fractures

Identifiers

PMID33543383
OpenAlexW3128353154

What OpenQuestion holds

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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.