Advancements in Automated Tooth Segmentation Using Deep Learning in MRI Scans

Posted: January 1, 2025
In a pilot study, an artificial intelligence model for tooth segmentation in magnetic resonance (MR) scans was developed and evaluated. The model, trained using the nnU-Net framework, achieved a precision of 0.867, sensitivity of 0.926, and Dice-Sørensen coefficient of 0.895. The study demonstrated moderate to high effectiveness in automated tooth segmentation, with challenges observed in scans with dental restorations due to image artefacts. This innovative approach showcases the potential for AI-enhanced dental imaging and highlights the importance of precision in dental diagnostics and treatment planning.

This article summary was generated by AI. To view the full article, click the link here: https://pubmed.ncbi.nlm.nih.gov/39589897/
Views: 6
Sponsors
Townie Perks
Townie® Poll
Who or what do you turn to for most financial advice regarding your practice?
  
The Dentaltown Team, Farran Media Support
Phone: +1-480-445-9710
Email: support@farranmedia.com
©2025 Dentaltown, a division of Farran Media • All Rights Reserved
9633 S. 48th Street Suite 200 • Phoenix, AZ 85044 • Phone:+1-480-598-0001 • Fax:+1-480-598-3450