Osteoarthritis of the hip is one of the most prevalent musculoskeletal disorders and gives rise to a large level of disability, carrying a significant burden for individuals' quality of life, society and healthcare provision systems. The research will develop novel image-processing techniques to identify pelvis shapes at highest risk of developing OA. Early diagnosis is essential for successful intervention, and we will provide practical techniques for automating this task using computed tomography (CT) images of the pelvis. We will achieve this by modelling the shape of the pelvis and classifying shapes at risk of early-onset osteoarthritis. To infer shapes at risk, we will exploit a set of two-hundred CT scans that have been annotated by medics.
|Effective start/end date||4/07/22 → 3/07/23|
- Engineering and Physical Sciences Research Council
RCUK Research Areas
- Image and Vision Computing
- Mathematical Analysis
- Medical Imaging
- Non-linear Systems Mathematics
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