Dental Imaging Data, AI Biomarkers and Clinical Validation – Research Collaboration

Riga Stradins University (RSU) Faculty of Dentistry, Latvia, is seeking international research and technology partners for Horizon Europe projects focused on AI-based medical imaging, imaging biomarkers, early disease detection, risk assessment and clinical validation.

Our team at the Faculty of Dentistry and the Institute of Stomatology offers clinical expertise and the potential to provide dental and maxillofacial imaging datasets, including cone-beam computed tomography (CBCT), panoramic and other dental radiographs, together with relevant clinical information, subject to data availability, ethical approvals and data protection requirements.

Our expertise and potential contributions include:

• Dental and maxillofacial imaging datasets (CBCT and conventional dental radiographs).

• Collection, preparation and clinical interpretation of imaging datasets for AI research.

• Expert image annotation, anatomical measurements and labelling.

• Clinical assessment of imaging biomarkers and their potential diagnostic value.

• Clinical validation of AI-based diagnostic and risk assessment tools.

• Experience in interdisciplinary medical technology and product development.

Relevant experience

Our research team has experience in developing an AI-based tool for osteoporosis risk assessment using dental CBCT images. The technology is designed to analyse mandibular cortical bone and identify patients who may be at increased risk of osteoporosis.

Developed in collaboration with AI technology partners, the tool has reached the laboratory prototype stage (TRL 4). Our involvement includes clinical data collection, image annotation, clinical evaluation and validation activities, as well as participation in the development of a medical technology towards clinical application.

Collaboration sought

We are interested in joining international research consortia working on AI-based imaging biomarkers, early disease detection, disease risk prediction and clinical decision support.

We are particularly interested in collaborating with dental universities, clinical institutions and research centres that have access to CBCT datasets and expertise in independent and multicentre clinical validation.

Collaboration with researchers in osteoporosis, bone health and metabolic bone diseases is also of particular interest, especially where imaging data can be linked to relevant clinical information and reference measurements, such as DXA.

We also welcome partnerships with AI developers, medical imaging researchers and technology organisations offering complementary expertise in algorithm development, imaging analysis and medical technology innovation.

Our goal is to contribute clinical expertise, dental imaging data, expert annotations and validation capabilities to collaborative research and the development of innovative, clinically relevant AI-based healthcare solutions.