Shape modelling for predicting risk of early-onset hip osteoarthritis

髋关节骨性关节炎是最常见的肌肉骨骼疾病之一，会导致很大程度的残疾，给个人的生活质量、社会和医疗保健提供系统带来重大负担。这项研究将开发新的图像处理技术来识别发生骨性关节炎风险最高的骨盆形状。早期诊断是成功介入的关键，我们将提供实用技术，使用骨盆的计算机断层扫描(CT)图像自动完成这项任务。我们将通过对骨盆的形状进行建模并对有早发性骨关节炎风险的形状进行分类来实现这一点。为了推断有风险的形状，我们将利用一组经过医务人员注释的200例CT扫描。

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.