V2I12P63

DIAR (Dental Implantology Assisting Robot) as a Futuristic Solution to Ensure an Accurate and Precise Dental Implant Abutment Placement

Brian Limantoro^1*, Muhammad Zulfian Yahya¹,  Bryan Moslem Saifullah¹, Zahiyah Wulan Supriyono¹, Andrey¹, Claire Godwin Rio¹, Celine Meyska Intan Nalani Simatupang¹

Abstract

The massive emergence of artificial intelligence (AI) in dentistry 4.0 necessitates a new generation of tools to meet the demands for enhanced precision, efficiency, and success rates, particularly in dental implantology. This paper introduces a conceptual model for a dental implantology AI–based assisting robot, designed to provide a structured and systematic masterplan for treatment, thereby delivering enhanced patient outcomes through minimally invasive procedures. The system’s core functionality relies on a sophisticated predictive algorithm that leverages post-imaging analysis to generate detailed treatment predictions and comprehensive identification reports. This process is highly reliant on integrated imaging modalities, including both extraneous periapical/panoramic radiographs and a dedicated, on-board cone-beam computed tomography (CBCT) scanner. The CBCT data, essential for multiplanar reconstruction and accurate bone measurement, is integrated into a surgical navigation system to facilitate precise three-dimensional implant placement, while also enabling crucial sensory nerve mapping to minimize the risk of nerve injury. For advanced machine intelligence, the robot utilises convolutional neural networks (CNN) as its deep learning method. CNN is trained on vast datasets (mega dataset) to achieve high accuracy in tasks such as implant type recognition and post-surgical assessment (e.g., peri–implant bone loss measurement). The system culminates in a precise treatment execution phase, supported by 3D guided placement (including potential CAD/CAM fabrication) and an automated robotic hand. Crucially, the system features haptic feedback and a control interface, giving the human operator tactile sensation and control over intricate tasks. Overall, the integration of CNN, CBCT, and haptic control is designed to significantly reduce human errors, leading to more reliable, consistent, and aesthetic results, improving osseointegration rates and optimizing the complete cycle of dental implant therapy.

Keywords:

Dental implantology, dental implantology assisting robot, dental implant abutment placement, digital AI