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Early Diagnosis of Osteoporosis Using Active Appearance Model and Metacarpal Radiogrammetry

机译:利用主动外观模型及御术术术早期诊断骨质疏松症

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Osteoporosis is a condition of fragile bone with an increased susceptibility to fracture. Since the gold standard method used for the diagnosis of osteoporosis, Dual X-ray Absorptiometry (DXA), is expensive and not widely available in low economies, there is a need for low cost approaches to detect bone loss in people. A new automated radiogrammetric method for early diagnosis of osteoporosis from a single hand radiograph is proposed. In this technique, the third metacarpal bone is segmented from hand X-ray images using Active Appearance Models (AAM). Points of interest acquired from the segmented bone are used to take radiogrammetric measurements, from which bone indices are calculated. Data used in this work was acquired from 138 subjects in two hospitals in India. Significant radiogrammetric features were selected using statistical analysis. The bone indices are observed to be significantly correlated with Bone Mineral Density (BMD) of the lumbar spine measured using DXA. Different classification models were trained using the significant features. The results obtained are promising and can be used as a cost effective diagnostic tool for early detection of osteoporosis.
机译:骨质疏松症是脆弱的骨骼的状况,对骨折的敏感性增加。由于用于诊断骨质疏松症的黄金标准方法,双X射线吸收测定量(DXA)是昂贵的并且在低经济体中不广泛使用,因此需要低成本的方法来检测人们的骨质损失。提出了一种新的自动放射线测量方法,用于从单手​​射线照片提取骨质疏松症的早期诊断。在该技术中,使用主动外观模型(AAM)从手X射线图像分段,第三款骨骨。从分段骨中获得的兴趣点用于采用放射性测量测量,从而计算骨骼指数。本工作中使用的数据是在印度的两家医院的138名科目中获得。使用统计分析选择了显着的放射线测量特征。观察到骨索引与使用DXA测量的腰椎的骨矿物密度(BMD)显着相关。使用重要特征培训不同的分类模型。获得的结果是有前途的,可用作早期检测骨质疏松症的成本效益的诊断工具。

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