Quantitative tooth crowding analysis in occlusal intra-oral photographs using a convolutional neural network.

The presented CNN-based model was able to quantify the crowding in the anterior segment of the lower dental arch and score the Little Irregularity Index from a single intra-oral photograph with a satisfactory reliability and accuracy. Application of this model may lead to more efficient and convenient orthodontic diagnostics.

Authors

Jan G.J.H. Schols (ORCID: https://orcid.org/0000-0002-4452-4389)
Gabriel Hertig
Raphael Patcas (ORCID: https://orcid.org/0000-0003-3906-9083)
Tong Xi (ORCID: https://orcid.org/0000-0002-9142-9253)
Niels van Nistelrooij
Shankeeth Vinayahalingam (ORCID: https://orcid.org/0000-0002-2679-3841)

Institutions

Radboud University Nijmegen (NL)
University of Zurich (CH)
Radboud University Medical Center (NL)
Humboldt-Universität zu Berlin (DE)

Publication Details

Journal: PubMed
Published: 2025-04-08
DOI: https://doi.org/10.1093/ejo/cjaf025
Citations: 1
Primary Topic: Dental Radiography and Imaging
Type: article
Field-Weighted Citation Impact: 1.79

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article

Quantitative tooth crowding analysis in occlusal intra-oral photographs using a convolutional neural network.

Jan G.J.H. Schols, Gabriel Hertig, Raphael Patcas, Tong Xi et al.

Apr 8, 2025

1 citations

PubMed

Dental Radiography and Imaging

1.79

article

Quantitative tooth crowding analysis in occlusal intra-oral photographs using a convolutional neural network.

Jan G.J.H. Schols, Gabriel Hertig, Raphael Patcas, Tong Xi, Niels van Nistelrooij, Shankeeth Vinayahalingam

April 8, 2025article en

1 citations

Abstract

The presented CNN-based model was able to quantify the crowding in the anterior segment of the lower dental arch and score the Little Irregularity Index from a single intra-oral photograph with a satisfactory reliability and accuracy. Application of this model may lead to more efficient and convenient orthodontic diagnostics.

PubMedVol. 47(3)

Radboud University Nijmegen (NL), University of Zurich (CH), Radboud University Medical Center (NL), Humboldt-Universität zu Berlin (DE)

Openalex Percentile: Top 17%

Dental Radiography and Imaging

1.79

DOI Source OpenAlex

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