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

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Abstract

Objectives

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

Materials and methods

Thirty 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.

Results

The 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.

Conclusions

The 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.

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Acknowledgements

The authors thank Espaço da Escrita (Pró-Reitoria de Pesquisa - UNICAMP) for the language services provided.

Funding

This study was supported by the Brazilian National Council for Scientific and Technological Development (CNPq) (grant #457536/2014-4) and the Federal Institute of Education, Science and Technology of São Paulo (IFSP) (grant #23305.008073.2018-58).

Author information

Authors and Affiliations

  1. Department 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

    Lucas Exposto Soares & Marcelo Andrade da Costa Vieira

  2. Department of Oral Diagnosis, Division of Oral Radiology, Piracicaba Dental School, University of Campinas, Av. Limeira, 901, Piracicaba, São Paulo, 13414-903, Brazil

    Deborah Queiroz Freitas

  3. Department of Stomatological Sciences, School of Dentistry, Federal University of Goiás, Av. Universitária s/n, Goiânia, Goiás, 74605-220, Brazil

    Kaique Leite de Lima, Lorena Rosa Silva & Fernanda Paula Yamamoto-Silva

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  1. Lucas Exposto Soares
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  2. Deborah Queiroz Freitas
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  3. Kaique Leite de Lima
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  4. Lorena Rosa Silva
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  6. Marcelo Andrade da Costa Vieira
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Contributions

All authors contributed to the study conception and design. Material preparation and data collection were performed by Lucas E. Soares, Deborah Q. Freitas, Kaique L. Lima, Lorena R. Silva, and Fernanda P. Yamamoto-Silva. The data analysis was performed by Lucas E. Soares and Deborah Q. Freitas. The proposed image processing framework was designed by Lucas E. Soares and Marcelo A. C. Vieira. The first draft of the manuscript was written by Lucas E. Soares, Deborah Q. Freitas, and Marcelo A. C. Vieira and all authors commented on previous versions of the manuscript. The study was supervised and reviewed by Marcelo A. C. Vieira, Deborah Q. Freitas and Fernanda P. Yamamoto-Silva. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Marcelo Andrade da Costa Vieira.

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Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the Research Ethics Committee of the Federal University of Goiás (#24810513.7.0000.5083) and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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For this type of study, formal consent is not required.

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The authors declare no competing interests.

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Soares, L.E., Freitas, D.Q., Lima, K.L. et al. Application of image processing techniques to aid in the detection of vertical root fractures in digital periapical radiography. Clin Oral Invest 25, 5077–5085 (2021). https://doi.org/10.1007/s00784-021-03820-z

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  • DOI: https://doi.org/10.1007/s00784-021-03820-z

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