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基于分形的小梁骨结构图像纹理分析

Fractal-based image texture analysis of trabecular bone architecture.

作者信息

Jiang C, Pitt R E, Bertram J E, Aneshansley D J

机构信息

Analogic Corporation, Peabody, MA 01960, USA.

出版信息

Med Biol Eng Comput. 1999 Jul;37(4):413-8. doi: 10.1007/BF02513322.

Abstract

Fractal-based image analysis methods are investigated to extract textural features related to the anisotropic structure of trabecular bone from the X-ray images of cubic bone specimens. Three methods are used to quantify image textural features: power spectrum, Minkowski dimension and mean intercept length. The global fractal dimension is used to describe the overall roughness of the image texture. The anisotropic features formed by the trabeculae are characterised by a fabric ellipse, whose orientation and eccentricity reflect the textural anisotropy of the image. Tests of these methods with synthetic images of known fractal dimension show that the Minkowski dimension provides a more accurate and consistent estimation of global fractal dimension. Tests on bone x-ray (eccentricity range 0.25-0.80) images indicate that the Minkowski dimension is more sensitive to the changes in textural orientation. The results suggest that the Minkowski dimension is a better measure for characterising trabecular bone anisotropy in the x-ray images of thick specimens.

摘要

研究基于分形的图像分析方法,以从立方骨标本的X射线图像中提取与小梁骨各向异性结构相关的纹理特征。使用三种方法量化图像纹理特征:功率谱、闵可夫斯基维数和平均截距长度。全局分形维数用于描述图像纹理的整体粗糙度。由小梁形成的各向异性特征由结构椭圆表征,其方向和偏心率反映图像的纹理各向异性。对已知分形维数的合成图像进行这些方法的测试表明,闵可夫斯基维数对全局分形维数提供了更准确和一致的估计。对骨X射线(偏心率范围0.25 - 0.80)图像的测试表明,闵可夫斯基维数对纹理方向的变化更敏感。结果表明,闵可夫斯基维数是表征厚标本X射线图像中小梁骨各向异性的更好度量。

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