BACKGROUND: Tooth segmentation on intraoral scanned (IOS) data is a prerequisite for clinical applications in digital workflows. Current state-of-the-art methods lack the robustness to handle variability in dental conditions. This study aims to propo...
OBJECTIVES: In the interpretation of panoramic radiographs (PRs), the identification and numbering of teeth is an important part of the correct diagnosis. This study evaluates the effectiveness of YOLO-v5 in the automatic detection, segmentation, and...
American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics
Jun 21, 2024
INTRODUCTION: The accuracy of tooth segmentation in intraoral scans is crucial for performing virtual setups and appliance fabrication. Hence, the objective of this study was to estimate and compare the accuracy of automated tooth segmentation genera...
OBJECTIVES: Segmentation of anatomical structures on dento-maxillo-facial (DMF) computed tomography (CT) or cone beam computed tomography (CBCT) scans is increasingly needed in digital dentistry. The main aim of this research was to propose and evalu...
Dental radiography is widely used in dental practices and offers a valuable resource for the development of AI technology. Consequently, many researchers have been drawn to explore its application in different areas. The current systematic review was...
OBJECTIVES: This systematic review and meta-analysis aimed to assess the current performance of artificial intelligence (AI)-based methods for tooth segmentation in three-dimensional cone-beam computed tomography (CBCT) images, with a focus on their ...
OBJECTIVE: The imbalanced nature of real-world datasets is an ongoing challenge in the field of machine and deep learning. In medicine and in dentistry, most data samples represent patients not affected by pathologies, and on imagery, pathologic imag...
BACKGROUND: Teeth identification has a pivotal role in the dental curriculum and provides one of the important foundations of clinical practice. Accurately identifying teeth is a vital aspect of dental education and clinical practice, but can be chal...
The present study tested the combination of mandibular and dental dimensions for sex determination using machine learning. Lateral cephalograms and dental casts were used to obtain mandibular and mesio-distal permanent teeth dimensions, respectively....
OBJECTIVES: This study aims to explore and discuss recent advancements in tooth reconstruction utilizing deep learning (DL) techniques. A review on new DL methodologies in partial and full tooth reconstruction is conducted.
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