Evaluation of an artificial intelligence-based model in diagnosing periodontal radiographic bone loss
- 01.04.2025
- Research
Erschienen in:
- Verfasst von
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Luanny de Brito Avelino Cassiano
Luanny de Brito Avelino Cassiano
- Department of Dentistry, Federal University of Rio Grande do Norte - UFRN, Natal, Brazil
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Jordão Paulino Cassiano da Silva
Jordão Paulino Cassiano da Silva
- Postgraduate Program in Electrical and Computer Engineering, Center of Technology, Natal, Brazil
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Agnes Andrade Martins
Agnes Andrade Martins
- Department of Dentistry, Federal University of Rio Grande do Norte - UFRN, Natal, Brazil
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Matheus Targino Barbosa
Matheus Targino Barbosa
- Postgraduate Program in Electrical and Computer Engineering, Center of Technology, Natal, Brazil
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Katryne Targino Rodrigues
Katryne Targino Rodrigues
- Department of Dentistry, Federal University of Rio Grande do Norte - UFRN, Natal, Brazil
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Ádylla Rominne Lima Barbosa
Ádylla Rominne Lima Barbosa
- Department of Dentistry, Federal University of Rio Grande do Norte - UFRN, Natal, Brazil
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Gabriela Ellen da Silva Gomes
Gabriela Ellen da Silva Gomes
- Department of Dentistry, Federal University of Rio Grande do Norte - UFRN, Natal, Brazil
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Paulo Raphael Leite Maia
Paulo Raphael Leite Maia
- Department of Dentistry, Federal University of Rio Grande do Norte - UFRN, Natal, Brazil
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Patrícia Teixeira de Oliveira
Patrícia Teixeira de Oliveira
- Department of Dentistry, Federal University of Rio Grande do Norte - UFRN, Natal, Brazil
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Maria Luiza Diniz de Sousa Lopes
Maria Luiza Diniz de Sousa Lopes
- Department of Dentistry, Federal University of Rio Grande do Norte - UFRN, Natal, Brazil
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Ivanovitch Medeiros Dantas da Silva
Ivanovitch Medeiros Dantas da Silva
- Department of Dentistry, Federal University of Rio Grande do Norte - UFRN, Natal, Brazil
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Ana Rafaela Luz de Aquino Martins
Korrespondierender Autor Ana Rafaela Luz de Aquino Martins
- Department of Dentistry, Federal University of Rio Grande do Norte - UFRN, Natal, Brazil
- Department of Dentistry, Federal University of Rio Grande do Norte, 59056-000, Natal, Brazil
- Erschienen in
- Clinical Oral Investigations | Ausgabe 4/2025
Abstract
Objective
To develop an artificial intelligence model based on convolutional neural network for detecting and measuring periodontal radiographic bone loss (RBL).
Materials and methods
Keypoint annotations were carried out in 595 digital bitewing radiographic images using a Computer Vision Annotation Tool. The dataset was splitted: 416 of these images were trained using the You Only Look Once version 8 architecture with pose estimation (YOLO-v8-pose), 119 images were destined for the validation set, and 60 images were used for the test set, resulting in a model capable of detecting keypoints related to the cementoenamel junction (CEJ) and alveolar bone crest (ABC). In order to evaluate the performance of the obtained model, the following metrics were analyzed: F1-Score, precision, sensitivity and mean average precision (mAP). Then, an algorithm was implemented to measure the RBL by calculating the Euclidean distance between CEJ and ABC.
Results
The model achieved an F1-Score of 66,89%, precision of 61,1%, a sensitivity of 73,9% and an mAP of 73.8%.
Conclusions
The developed model and its algorithm for identifying and measuring periodontal radiographic bone loss demonstrated promising performance, thereby presenting a potential tool for assisting in periodontal diagnosis. Further studies comparing the developed model with manual measurements performed by specialists are necessary for its validation.
Clinical relevance
Applying artificial intelligence in clinical dental practice can support diagnosis, streamline clinical workflows, and inform treatment planning, representing a significant advancement in dental automation.
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- Titel
- Evaluation of an artificial intelligence-based model in diagnosing periodontal radiographic bone loss
- Verfasst von
-
Luanny de Brito Avelino Cassiano
Jordão Paulino Cassiano da Silva
Agnes Andrade Martins
Matheus Targino Barbosa
Katryne Targino Rodrigues
Ádylla Rominne Lima Barbosa
Gabriela Ellen da Silva Gomes
Paulo Raphael Leite Maia
Patrícia Teixeira de Oliveira
Maria Luiza Diniz de Sousa Lopes
Ivanovitch Medeiros Dantas da Silva
Ana Rafaela Luz de Aquino Martins
- Publikationsdatum
- 01.04.2025
- Verlag
- Springer Berlin Heidelberg
- Erschienen in
-
Clinical Oral Investigations / Ausgabe 4/2025
Print ISSN: 1432-6981
Elektronische ISSN: 1436-3771 - DOI
- https://doi.org/10.1007/s00784-025-06283-8
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