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A Postoperative Evaluation Guideline for Computer-Assisted Reconstruction of the Mandible

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Published on: January 28, 2020

Optimizing Ridge Augmentation With AI-Generated Models: A Case Report With Technical Note.

Vasilios Alevizakos¹, Stephan Knörzer², Roman Krammer²

¹Research Centre for Digital Technologies in Dentistry and CAD/CAM Danube Private University Krems Austria.

Clinical Case Reports

|December 22, 2025

Summary

AI-generated 3D models enhance ridge augmentation surgery by improving accuracy and reducing bone exposure. These digital tools aid patient understanding but require clinical expertise, validation, and training for safe implementation.

Keywords:

alveolar ridge augmentation artificial intelligence cone beam computed tomography dental implants three‐dimensional printing

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Area of Science:

Oral and Maxillofacial Surgery
Medical Imaging
Computer-Aided Design

Background:

Ridge augmentation is a common procedure in oral surgery.
Accurate pre-operative planning is crucial for successful outcomes.
Patient comprehension of surgical plans can be challenging.

Purpose of the Study:

To evaluate the impact of AI-generated 3D models on surgical accuracy in ridge augmentation.
To assess the benefits of AI-driven visual planning for patient understanding.
To explore the role of AI in supporting clinical decision-making.

Main Methods:

Development of AI algorithms for generating patient-specific 3D models from imaging data.
Integration of 3D models into surgical planning workflows.
Comparison of surgical outcomes and patient feedback with and without 3D model utilization.

Main Results:

AI-generated 3D models demonstrated improved surgical accuracy.
Reduced intraoperative bone exposure was observed.
Enhanced patient understanding and engagement with the surgical plan.

Conclusions:

AI-generated 3D models are valuable tools for ridge augmentation, enhancing precision and patient communication.
These models augment, but do not substitute, surgeon expertise.
Continued validation, training, and ethical considerations are necessary for clinical integration.