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Human Spinal Column Diagnostic Parameter Identification Using Geometrical Model of the Vertebral Body ?

机译:使用椎体的几何模型的人脊柱诊断参数识别

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摘要

A geometric model and related methods to easily define patient specific vertebral body models have been introduced in our previous studies. This paper proposes an angle measurement method that can be fully automated after the definition of the patient specific vertebral body model. A Principal Component Analysis based algorithm allowing the quick identification of the symmetry plane of the human spline is also developed and described. The clinical dataset used to analyse and validate the models and methods introduced consists of 39 patients’ lumbar section of the spinal column with 195 vertebrae.In terms of angle measurement the proposed geometric model and the measurement method is proven to be accurate enough for clinical diagnostics, the average mean value of the measurement error 0.15° and 0.75° comparing the measurements to the two reference datasets. The average standard deviation of the error was around 2.50° that is almost the same as the average standard deviation of the two reference datasets (2.34°).
机译:在我们以前的研究中介绍了易于定义患者特异性椎体模型的几何模型和相关方法。本文提出了一种角度测量方法,可以在患者特异性椎体模型的定义之后完全自动化。还开发并描述了一种基于基于组分分析的基于组分分析允许快速识别人样条曲线的对称平面。用于分析和验证型号和方法的临床数据集由195个椎骨的39名患者腰部截面组成。角度测量方面,所提出的几何模型和测量方法被证明足以准确临床诊断,测量误差的平均平均值0.15°和0.75°比较两个参考数据集的测量值。误差的平均标准偏差约为2.50°,与两个参考数据集的平均标准偏差几乎相同(2.34°)。

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