Introduction to AI in Dental Implant Planning
The integration of artificial intelligence (AI) in dental implant planning is revolutionizing the field by enhancing diagnostic accuracy and efficiency. A recent study assessed the performance of two AI models, Faster R-CNN and YOLOv7, in analyzing images from four different dental imaging software platforms. The dataset comprised 332 implant position images sourced from 184 CBCT scans.
For developing the models, 300 images were processed using DentiPlan Pro 3.7. Testing involved analyzing 32 additional images using four software programs: DentiPlan Pro Plus 5.0, Implastation, and Romexis 6.0. The performance metrics included detection rate, accuracy, precision, recall, F1 score, and the Jaccard Index (JI). Results showed that while Faster R-CNN achieved superior accuracy, YOLOv7 had higher detection rates but lower precision. The findings highlighted the importance of standardized preprocessing in AI models for consistent outcomes.
Conclusion and Future Directions
This study underscores the potential of AI-driven solutions in dental implant planning, advocating for further research. Despite no significant statistical differences between the two models, they can each be utilized effectively based on the specific needs for accuracy or detection. Notably, variations in image rendering algorithms across software platforms significantly impacted model performance.
For more details, check the full study here.
