Hybrid Expert System Using Knowledge Rules and Image Processing for Dental Implant Evaluation

DOI

10.2991/978-94-6463-948-3_35How to use a DOI?

Keywords

Artificial intelligence in dentistry; Dental implant; Hybrid expert system; Image processing; Knowledge-based rules; Radiographic analysis

Abstract

The long-term stability and aesthetic success of dental implants rely heavily on precise evaluation techniques. To address this, need a hybrid expert system is introduced that integrates rule-based clinical knowledge with automated image analysis. It’s aiming to improve diagnostic accuracy and support practitioners during implant assessment. The framework consists of two complementary modules. The first, a knowledge-based component, utilizes structured decision rules developed from clinical guidelines, expert opinions, and best practice standards to enable systematic reasoning. The second module employs image processing methods to analyse dental radiographs through segmentation and feature extraction, enabling detection of implant boundaries, measurement of bone support, and identification of peri-implant conditions. Outputs from both modules are combined to deliver comprehensive diagnostic insights.

The system was tested using a dataset of clinical radiographs, and results indicate that the hybrid model provides superior performance compared to standalone rule-based or image-only approaches. The integration of symbolic reasoning with quantitative imaging significantly improved sensitivity, specificity, and overall evaluation consistency while reducing diagnostic variability. This hybrid expert system presents a reliable and scalable tool for dental implant assessment, with strong potential to enhance clinical decision-making. Its promote standardized diagnostic practices and establish a foundation for future AI-driven innovations in digital dentistry.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Ashwini Khairkar
AU  - Sonali Kadam
PY  - 2026
DA  - 2026/01/06
TI  - Hybrid Expert System Using Knowledge Rules and Image Processing for Dental Implant Evaluation
BT  - Proceedings of the International Conference on Sustainable Innovation with Artificial Intelligence and Machine Learning 2025 (ICSIAIML 2025)
PB  - Atlantis Press
SP  - 490
EP  - 503
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-948-3_35
DO  - 10.2991/978-94-6463-948-3_35
ID  - Khairkar2026
ER  -