Combining the measurement of bone mineral density (BMD) and the classification of the trabecular structure in cancellous bone improves the estimation of the degree of osteoporosis. A fractal method for the automatic quantitative classification of the trabecular structure in midvertebral slices of lumbar vertebrae is introduced. This method is based on the computation of the fractal dimension (box counting method) for varying binarization thresholds. Radiographic images from 30 lumbar vertebrae and CT images from an additional 16 lumbar vertebrae were analysed by calculating the dimension D in dependency of the threshold value T. The function D(T) was normalized by the average image grey value, eliminating the bone mineral density from the computations. The results show that the images of the lumbar vertebrae have fractal properties, and the function D(T) has a typical behaviour that allows the discrimination of the degree of osteoporosis. With two parameters extracted from the function D(T) the correlation coefficients with BMD were both -79% for the radiographic images, and -93% and -91% for the CT data, respectively.

译文

结合骨密度 (BMD) 的测量和松质骨中小梁结构的分类,可以改善对骨质疏松症程度的估计。介绍了一种用于腰椎中段椎板小梁结构自动定量分类的分形方法。此方法基于分形维数 (盒计数法) 的计算来改变二值化阈值。通过根据阈值T计算尺寸D来分析来自30个腰椎的放射线图像和来自另外16个腰椎的CT图像。函数D(T) 通过平均图像灰度值进行归一化,从而从计算中消除了骨矿物质密度。结果表明,腰椎图像具有分形特性,函数D(T) 具有典型的行为,可以区分骨质疏松症的程度。利用从函数D(T) 中提取的两个参数,射线照相图像与BMD的相关系数分别为-79%,CT数据与-93% 和-91%。

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