Shape modelling for predicting risk of early-onset hip osteoarthritis

用于预测早发性髋骨关节炎风险的形状建模

• 批准号: EP/W005565/1
• 负责人: Tony Shardlow
• 金额: $ 9.95万
• 依托单位: University of Bath
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FW005565%2F1
• 关键词: Shape; modelling; predicting; risk; early

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.

髋关节骨关节炎是最常见的肌肉骨骼疾病之一，并引起大程度的残疾，对个人的生活质量、社会和医疗保健提供系统造成重大负担。该研究将开发新的图像处理技术，以识别患OA风险最高的骨盆形状。早期诊断对于成功干预至关重要，我们将提供实用的技术，使用骨盆计算机断层扫描（CT）图像自动执行这项任务。我们将通过模拟骨盆的形状并对早发性骨关节炎风险的形状进行分类来实现这一目标。为了推断出有风险的形状，我们将利用一组200个CT扫描结果，这些扫描结果已经被医生注释过了。