Biomechanical modelling and computational imaging to identify different causes of back pain in large epidemiological studies

Project description

Novel image analysis algorithms to identify causes of chronic back pain

Chronic back pain, a major source of disability worldwide, has biomechanical, inflammatory, neurological and psychological causes. Conventional imaging and evaluation cannot point to a particular cause of back pain, but biomechanical models are capable of distinguishing between different aetiologies. The EU-funded iBack-epic aims to use novel image analysis techniques to identify biomechanical and inflammatory causes of back pain in a large cohort of participants. The study will capitalise on the recently developed spine labelling and segmentation algorithms based on deep learning to calculate individual biomechanical, functional and morphometric parameters of the spine. The quantitative image-based parameters will help discriminate between normal ageing and pathologic degeneration and identify conditions linked to the development of chronic back pain.

Fields of science

• medical and health sciences › basic medicine › physiology › pathophysiology
• natural sciences › computer and information sciences › artificial intelligence › machine learning › deep learning
• engineering and technology › medical engineering › diagnostic imaging › magnetic resonance imaging

Programme(s)

• HORIZON.1.1 - European Research Council (ERC) Main Programme

Topic(s)

• ERC-2021-COG - ERC CONSOLIDATOR GRANTS

Call for proposal

ERC-2021-COG

See other projects for this call

Funding Scheme

HORIZON-AG - HORIZON Action Grant Budget-Based

Coordinator

KLINIKUM RECHTS DER ISAR DER TECHNISCHEN UNIVERSITAT MUNCHEN

Net EU contribution

€ 1 999 993,00

Address

Ismaninger Strasse 22
81675 Muenchen
Germany

Region

Bayern › Oberbayern › München, Kreisfreie Stadt

Activity type

Higher or Secondary Education Establishments

Links

Other funding

€ 0,00