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Segmentation and Determination of Joint Space Width in Foot Radiographs

机译:足部X线照片中关节间隙宽度的分割和确定

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Joint damage in rheumatoid arthritis is frequently assessed using radiographs of hands and feet. Evaluation includes measurements of the joint space width (JSW) and detection of erosions. Current visual scoring methods are time-consuming and subject to inter- and intra-observer variability. Automated measurement methods avoid these limitations and have been fairly successful in hand radiographs. This contribution aims at foot radiographs. Starting from an earlier proposed automated segmentation method we have developed a novel model based image analysis algorithm for JSW measurements. This method uses active appearance and active shape models to identify individual bones. The model compiles ten submodels, each representing a specific bone of the foot (metatarsals 1-5, proximal phalanges 1-5). We have performed segmentation experiments using 24 foot radiographs, randomly selected from a large database from the rheumatology department of a local hospital: 10 for training and 14 for testing. Segmentation was considered successful if the joint locations are correctly determined. Segmentation was successful in only 14%. To improve results a step-by-step analysis will be performed. We performed JSW measurements on 14 randomly selected radiographs. JSW was successfully measured in 75%, mean and standard deviation are 2.30±0.36mm. This is a first step towards automated determination of progression of RA and therapy response in feet using radiographs.
机译:类风湿性关节炎的关节损伤经常使用手和脚的X光片进行评估。评估包括关节间隙宽度(JSW)的测量和腐蚀的检测。当前的视觉评分方法非常耗时,并且受观察者之间和观察者内部差异的影响。自动化的测量方法避免了这些限制,并且在手工X射线照相中已经相当成功。该贡献主要针对脚部X光片。从较早提出的自动分割方法开始,我们为JSW测量开发了一种基于模型的新颖图像分析算法。该方法使用活动外观和活动形状模型来识别单个骨骼。该模型编译十个子模型,每个子模型代表脚的特定骨骼((骨1-5,近端指骨1-5)。我们使用了24英尺的X射线照片进行了分割实验,这些X射线照片是从当地医院风湿病科的大型数据库中随机选择的:10个用于训练,14个用于测试。如果正确确定了关节位置,则认为分割成功。细分成功率仅为14%。为了改善结果,将进行逐步分析。我们对14个随机选择的X射线照片进行了JSW测量。成功测量了JSW的75%,平均值和标准偏差为2.30±0.36mm。这是使用放射线照片自动确定RA进展和足部治疗反应的第一步。

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