Title
Marginal and internal fit of endo-crowns: AI-based evaluation
Authors
Mahesh Suganna Golgeri1, Gurpreet Singh2,*, Pooja Arora3, Urja Ahuja4, Arun Kharavela Mohanty5 & Abhinav Patel6
Affiliation
1Department of Prosthodontics, Riyadh ELM University, Riyadh, Kingdom Saudi Arabia; 2Private practitioner, GDC Patiala, Punjab, India; 3Department of Periodontology, Adesh Institute of Dental Science and Research, Bathinda, Punjab, India; 4Department of Conservative Dentistry and Endodontics, Uttaranchal Medical and Dental Research Institute, Dehradun, Uttarakhand, India; 5Department of Prosthodontics, Crown and Bridge, Kalinga Institute of Dental Sciences, Bhubaneswar, India; 6Department of Public Health Dentistry, Rungta College of Dental Sciences and Research, Bhilai, Chhattisgarh, India; *Corresponding author
Mahesh Suganna Golgeri - E-mail: maheshgolgeri@gmail.com;
Gurpreet Singh - E-mail: Gs2851986@gmail.com
Pooja Arora - E-mail: drpoojaarora786@gmail.com
Urja Ahuja - E-mail: Urja.ahu@gmail.com
Arun Kharavela Mohanty - E-mail: docmohanty89@gmail.com
Abhinav Patel - E-mail: patel.abhinav38@gmail.com
Article Type
Research Article
Date
Received August 1, 2025; Revised August 31, 2025; Accepted August 31, 2025, Published August 31, 2025
Abstract
The internal and marginal adaptation of endo-crown restorations fabricated using traditional and digital impression techniques is described. Artificial intelligence (AI) was used to analyze high-resolution imaging data obtained through digital scanning and micro-computed tomography. Results showed that endo-crowns produced with digital impressions exhibited superior fit compared to those made with conventional methods. AI-based analysis provided more accurate and consistent measurements than manual evaluation. Thus, we show AI's potential to enhance the precision of prosthodontic assessments.
Keywords
Endo-crown, marginal adaptation, internal adaptation, impression techniques, digital impressions, conventional impressions, artificial intelligence (AI), Micro-CT CAD/CAM dentistry
Citation
Golgeri et al. Bioinformation 21(8): 2533-2536 (2025)
Edited by
Akshaya Ojha
ISSN
0973-2063
Publisher
License
This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.
