Automated Deep Machine Learning Platform for Early Osteoporosis Risk Assessment Using Cone-Beam Computed Tomography Images of the Craniofacial Region (OsteoXplore)

Osteoporosis is a common disease of the skeletal system that reduces bone strength and significantly increases the risk of fractures. It particularly affects people over 50 years of age and can lead to disability, a decline in quality of life, and even premature death. Although early diagnosis is crucial, the current primary method for detecting osteoporosis is not widely accessible and is unsuitable for regular screening.

The project aims to develop OsteoXplore, an artificial intelligence platform that would allow to identify the osteoporosis risk by using regular dental 3D X-ray images that had been taked already. By analyzing the thickness of the mandibular cortical bone layer and other indicators, the system will automatically identify patients with possible bone mineral density reduction using deep machine learning. The platform will integrate several image analysis modules into a unified system, and its performance will be tested with patient data acquired from various devices.

This approach would allow dental examinations to be used not only for assessing oral health but also for the early detection of osteoporosis. By integrating the solution into dental practice, it would be possible to identify at-risk patients early and refer them for further diagnosis and treatment.

– Early detection of osteoporosis risk using existing dental examinations

Broader and more accessible osteoporosis screening for the public

– The solution promotes timely treatment, which reduces the risk of fractures and improves quality of life

– Reduced healthcare costs by preventing complications and severe fractures