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 b...
Dental diseases are one of the most common diseases that affect humans. Clinicians employ several techniques for diagnosing and monitoring dental diseases, with intra-oral periapical (IOPA) radiographs being among the most commonly utilized methods. ...
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Sep 25, 2025
This paper examines the current challenges in computed tomography (CT), with a critical exploration of existing methodologies from a mathematical perspective. Specifically, it aims to identify research directions to enhance image quality in low-dose,...
BACKGROUND: Evaluating the quality of root canal filling (RCF) performed by dental students in preclinical settings is a time-consuming process for clinicians and is often subjectively assessed.
OBJECTIVES: This study assessed the performance of chatbots in the screening step of a systematic review (SR) with an exemplary focus on tooth segmentation on dental radiographs using artificial intelligence (AI).
BACKGROUND: With the growing capabilities of language models like ChatGPT to process text and images, this study evaluated their accuracy in detecting supernumerary teeth on periapical radiographs. A customized GPT-4V model (CGPT-4V) was also develop...
BACKGROUND: Artificial intelligence (AI) is transforming diagnostic imaging in dentistry. This systematic review evaluates existing literature on augmented intelligence in dentomaxillofacial radiology, focusing on its influence on human collaboration...
OBJECTIVES: Annotating carious lesions on images is challenging. For artificial intelligence (AI) applications, the aggregation of heterogeneous multi-examiner annotations into one single annotation (e.g. via majority voting, MV) is usually needed. W...
OBJECTIVES: This study evaluates and compares the performance of ChatGPT-3.5, ChatGPT-4 Omni (4o), Google Bard, and Microsoft Copilot in responding to text-based multiple-choice questions related to oral radiology, as featured in the Dental Specialty...
OBJECTIVE: This study evaluated ResNet-50 and U-Net models for detecting and segmenting vertical misfit in dental implant crowns using periapical radiographic images.
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