Shreya Kothari¹*, Veenadevi Thonthula², Valliammai Rajendran³, Aishwarya Dham⁴ and Hridya Jayaprakash⁵

¹BDS, MPH, Ann Arbor, Michigan, USA
²BDS, General Dentist (India), Orchards Blvd SW, Edmonton, Alberta T6X1Y9
³MDS, Periodontist, Sri Karpaga Vinaayak Dental Clinic, Trichy, Tamil Nadu, India
⁴MDS, Senior Lecturer, Department of Periodontology, Hazaribagh College of Dental Sciences and Hospital, Demotand, Hazaribagh, India
⁵MDS, Periodontist, Clove Dental, Sholinganallur, Chennai, Tamil Nadu, India

*Corresponding Author: Shreya Kothari, BDS, MPH, Ann Arbor, Michigan, USA

Received: May 29, 2025; Published: June 20, 2025

Abstract

AI-enhanced Cone-Beam Computed Tomography (CBCT) analysis is transforming dental 1study examines the revolutionary influence of AI algorithms combined with CBCT imaging, highlighting its capacity to automate anatomical landmark identification, assess bone quality and volume, forecast implant success, and tailor treatment strategies. AI-driven CBCT analysis enhances implant placement by diminishing operator reliance and eliminating diagnostic inaccuracies, resulting in a more efficient, objective, and tailored methodology. The review highlights that this technological convergence not only optimizes clinical workflows but also enhances patient safety and happiness, establishing AI as a crucial instrument in the future of implant dentistry.

Keywords:Artificial Intelligence, CBCT Analysis, Dental Implant

References

1. Gulati M., et al. “Computerized implant-dentistry: Advances toward automation”. Journal of Indian Society of Periodontology 1 (2015): 5-10.
2. Macrì M., et al. “The Role and Applications of Artificial Intelligence in Dental Implant Planning: A Systematic Review”. Bioengineering (Basel)8 (2024): 778.
3. Fan W., et al. “The Application of Deep Learning on CBCT in Dentistry”. Diagnostics (Basel)12 (2023): 2056.
4. Pauwels R., et al. “CBCT-based bone quality assessment: are Hounsfield units applicable?” Dentomaxillofacial Radiology 1 (2015): 20140238.
5. Rajan RSS., et al. “Evaluating the Role of AI in Predicting the Success of Dental Implants Based on Preoperative CBCT Images: A Randomized Controlled Trial”. Journal of Pharmacy and Bioallied Sciences 1 (2024): S886-S888.
6. Scolozzi P., et al. “Computer-Aided Design and Computer-Aided Modeling (CAD/CAM) for Guiding Dental Implant Surgery: Personal Reflection Based on 10 Years of Real-Life Experience”. Journal of Personalized Medicine 1 (2023): 129.
7. Albrektsson T., et al. “Implications of considering peri-implant bone loss a disease, a narrative review”. Clinical Implant Dentistry and Related Research 4 (2022): 532-543.
8. Lin PY., et al. “The use of augmented reality (AR) and virtual reality (VR) in dental surgery education and practice: A narrative review”. The Journal of Dental Sciences 2 (2024): S91-S101.
9. Mennella C., et al. “Ethical and regulatory challenges of AI technologies in healthcare: A narrative review”. Heliyon4 (2024): e26297.
10. Alyami MH. “The Applications of 3D-Printing Technology in Prosthodontics: A Review of the Current Literature”. Cureus9 (2024): e68501.
11. Karnik AP., et al. “Transforming Prosthodontics and oral implantology using robotics and artificial intelligence”. Frontiers in Oral Health 5 (2024): 1442100.

Citation

Citation: Shreya Kothari., et al. “Artificial Intelligence-Enabled CBCT Analysis: A Game-Changer for Dental Implant Optimization". Acta Scientific Dental Sciences 9.7 (2025): 15-17.

Copyright

Copyright: © 2025 Shreya Kothari., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.