Project Details
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Ultrasound assessment of buccal bone and mucosal thickness using artificial intelligence aided segmentation in dental implantology

Subject Area Dentistry, Oral Surgery
Biomedical Systems Technology
Term since 2022
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 505784181
 
The aim of this project is to evaluate the feasibility of artificial intelligence (AI) assisted B-mode ultrasound based digital monitoring to assess buccal peri-implant tissues in an ex-vivo porcine model, using parameters that enable a future clinical trial. The clinical relevance of this study is to create future conditions for any dentist to accurately measure peri-implant tissues with ultrasound, even without experience with this technology. The difficulty would be the evaluation of the ultrasound image. Therefore, the aim of this project is to create a tool based on AI to facilitate the measurements. The AI-based method is expected to help robustly segment the anatomical structures after US scanning, co-registration with a-priori information and evaluation in comparison with earlier clinical data, save time and making the ultrasound technology more user-friendly and feasible in clinical practice. The hypothesis is that B-mode ultrasound measurements present agreement with cone-beam computed tomography and direct measurements in a way it can be utilized as a supplementary tool to monitor peri-implant tissue dimensions in daily clinical routine. For the clinical assessment of buccal bone and mucosal thickness, only 2D distances have to be measured at defined positions. 3D ultrasound-based reconstructions add just little value but requires a great deal of equipment. In contrast, the use of B-mode ultrasound is widespread, easier to apply, and in recent years the signal-to-noise ratio has greatly improved. B-mode ultrasound probes offer the advantage of being much smaller than 3D probes and thus greatly simplify intraoral buccal measurement. However, unlike 3D ultrasound, B-mode ultrasound provides only a single (2D) image. Whereas this can be sufficient for 2D monitoring of peri-implant mucosa thickness, solutions for 3D-registration with the crown-implant construct and a reproducible and intuitive alignment of the ultrasound-probe need to be developed and evaluated. Thus, two further hypotheses have to be evaluated: (1) An accurate and robust registration process can be achieved using B-Mode US; and (2) A fully automatic robust processing and measurement can be achieved using AI.
DFG Programme Research Grants
International Connection Austria
 
 

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