Evaluating vision transformers and convolutional neural networks in the context of dental image processing: a systematic review.

ABSTRACT:

Background

The aim of this systematic review is to compare the efficacy of convolutional neural networks (CNN) and Vision Transformers (ViT) in the field of dental imaging, in order to examine in depth the potential, advantages, and limitations of both models in this domain.

Methods

The search strings used in the study were "(("Vision Transformer" OR ViT OR "Transformer architecture") AND ("Convolutional Neural Network" OR CNN OR ConvNet) AND (Dental OR Dentistry OR "Maxillofacial" OR "Oral Radiology") AND (Image OR Imaging OR Radiograph))". The search was conducted in January 2025. Two investigators independently evaluated the full texts of all eligible articles and excluded those that did not meet the inclusion/exclusion criteria.

Results

Of 2596 articles, 21 met th

SUBMITTER: Felek T 

PROVIDER: S-EPMC12522997 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature