Innovative Applications of AI and 3D Printing in Digital Dentistry: Enhancing Accuracy and Efficiency in Dental Care
Digital dentistry has significantly transformed the way dental professionals deliver patient care by integrating digital technologies into various aspects of the field, such as diagnosis, treatment planning, and restoration. This includes a broad array of technologies like computer-aided design and manufacturing (CAD/CAM), 3D printing, and artificial intelligence (AI), all of which are rapidly advancing and reshaping dental practice. Digital dentistry has ushered in greater precision, accuracy, and efficiency in patient care, leading to improved outcomes. While 3D printing has transformed industries, including dentistry, it still has several drawbacks and limitations. Here are some of the current challenges associated with 3D printing technology: 1) Complex Design Process, 2) Manual Design Adjustments, 3) Limited resolution and occasional inaccuracies in 3D prints, affecting precision in applications. To address these issues, we propose an AI-enabled framework that provides a simplified process to ensure success and minimize human error. Users can quickly import an STL file into the software, select the desired application, and begin printing within seconds. The system automatically analyzes the 3D object, adjusting its orientation and generating supports for splints, crowns, bridges, and surgical guides. In this paper, we analyze the impact of integrating artificial intelligence into the 3D printing workflow for digital dentistry. We focus on how AI can enhance the precision, efficiency, and reliability of dental prosthetics and restorations by automating critical steps that were traditionally manual and prone to errors. Specifically, our proposed framework streamlines the design process by automatically detecting complex geometries, optimizing support structures, and adjusting printing parameters in real time. This AI-enabled approach not only reduces the number of design iterations but also ensures higher resolution and accuracy, overcoming the limitations of conventional 3D printing methods.
Authors
- Yuqing Lou (ORCID: https://orcid.org/0000-0001-9218-2718)
- Yu Bai (ORCID: https://orcid.org/0000-0003-1542-0297)
- Kevin Huang (ORCID: https://orcid.org/0000-0002-8136-1195)
- G. Rodríguez Martínez (ORCID: https://orcid.org/0000-0002-0575-3592)
Institutions
- California State University, Fullerton (US)
Publication Details
- Published
- 2024-12-06
- DOI
- https://doi.org/10.1109/iiki65561.2024.00048
- Citations
- 1
- Primary Topic
- Dental Research and COVID-19
- Type
- article
- Field-Weighted Citation Impact
- 0.85