Optimized classification of dental implants using convolutional neural networks and pre-trained models with preprocessed data

Preprocessing steps, coupled with data augmentation, enhanced classification performance, ensuring robustness across models. CRF and CNN were the top-performing classifiers, with VGG16 excelling among pre-trained models. These results highlight the importance of data augmentation and preprocessing in improving dental implant classification accuracy.

Authors

Nasim Razavi (ORCID: https://orcid.org/0000-0003-1347-9156)
Hossein Najaf-Zadeh (ORCID: https://orcid.org/0000-0001-7411-8480)
Mehdi Goodarzi
Zahra Raeisi (ORCID: https://orcid.org/0009-0002-2334-3228)
Reza Ahmadi Lashaki (ORCID: https://orcid.org/0009-0005-7570-8884)

Institutions

Tabriz University of Medical Sciences (IR)
University of Tabriz (IR)
Becton Dickinson (Canada) (CA)
North Khorasan University of Medical Sciences (IR)
Islamic Azad University, Sepidan

Publication Details

Journal: BMC Oral Health
Published: 2025-04-11
DOI: https://doi.org/10.1186/s12903-025-05704-0
Citations: 12
Primary Topic: Dental Radiography and Imaging
Type: article
Field-Weighted Citation Impact: 21.49

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article

Optimized classification of dental implants using convolutional neural networks and pre-trained models with preprocessed data

Nasim Razavi, Hossein Najaf-Zadeh, Mehdi Goodarzi, Zahra Raeisi et al.

Apr 11, 2025

12 citations

BMC Oral Health

Dental Radiography and Imaging

21.49

article

Optimized classification of dental implants using convolutional neural networks and pre-trained models with preprocessed data

Nasim Razavi, Hossein Najaf-Zadeh, Mehdi Goodarzi, Zahra Raeisi, Reza Ahmadi Lashaki

April 11, 2025article en

12 citations

Abstract

Preprocessing steps, coupled with data augmentation, enhanced classification performance, ensuring robustness across models. CRF and CNN were the top-performing classifiers, with VGG16 excelling among pre-trained models. These results highlight the importance of data augmentation and preprocessing in improving dental implant classification accuracy.

BMC Oral HealthVol. 25(1)

Tabriz University of Medical Sciences (IR), University of Tabriz (IR), Becton Dickinson (Canada) (CA), North Khorasan University of Medical Sciences (IR), Islamic Azad University, Sepidan

Openalex Percentile: Top 0%

Dental Radiography and Imaging

21.49

DOI Open Access PDF OpenAlex

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Optimized classification of dental implants using convolutional neural networks and pre-trained models with preprocessed data — Nasim Razavi, Hossein Najaf-Zadeh, et al. · BMC Oral Health (2025) | TGRS Research Map | TGRS