AI-Based Dental Implant Detection and Numbering
What's NEW
•
12m
This research article details the development and testing of an artificial intelligence (AI) model designed to detect and number dental implants in panoramic radiographs. Utilizing a large dataset of radiographs and the YOLOv8 deep learning algorithm, the researchers trained two models: one for implant segmentation and one for implant numbering within specific jaw regions. The models demonstrated high accuracy in both tasks, achieving precision, recall, and F1-scores above 90% in most cases. The study highlights the potential for this AI model to improve the efficiency and accuracy of dental implant assessments in clinical practice, though further validation with more diverse datasets is recommended. The authors compared the YOLOv8 model's performance to other state-of-the-art models, showing YOLOv8's superiority.
Up Next in What's NEW
-
Debunking the 10,000-Hour Rule-VEED
This article from Six Seconds challenges Malcolm Gladwell's popular "10,000 Hour Rule," arguing that it oversimplifies the path to expertise. The authors contend that the number of hours is arbitrary and that factors like genetics, age of starting, and the quality of practice (deliberate practice...
-
DentalTV Literature Club Trailer
Discover Literature Club on DentalTV, your go-to series for mastering dental research and evidence-based practices. Simplify literature searches, analyze studies, and apply insights to elevate your clinical skills. Led by experts, this approachable series bridges research and practice, empowering...
-
AI-Powered Diagnosis of Temporomandib...
This research paper details the development and validation of an artificial intelligence (AI) model for automated diagnosis and classification of temporomandibular joint degenerative joint disease (TMJ DJD) using cone beam computed tomography (CBCT) images. The AI model, based on the YOLOv10 algo...
