Medical University of Graz, Department of Radiology, Division of Neuroradiology, Vascular and Interventional Radiology, Graz, Austria.
University of Graz, Department of Psychology, Graz, Austria.
Sci Rep. 2018 Apr 3;8(1):5431. doi: 10.1038/s41598-018-23769-6.
Fractal analysis is a widely used tool to analyze the geometrical complexity of biological structures. The geometry of natural objects such as plants, clouds, cellular structures, blood vessel, and many others cannot be described sufficiently with Euclidian geometric properties, but can be represented by a parameter called the fractal dimension. Here we show that a specific estimate of fractal dimension, the correlation dimension, is able to describe changes in the structural complexity of the human brain, based on data from magnetic resonance diffusion imaging. White matter nerve fiber bundles, represented by tractograms, were analyzed with regards to geometrical complexity, using fractal geometry. The well-known age-related change of white matter tissue was used to verify changes by means of fractal dimension. Structural changes in the brain were successfully be observed and quantified by fractal dimension and compared with changes in fractional anisotropy.
分形分析是一种广泛用于分析生物结构几何复杂性的工具。植物、云、细胞结构、血管等自然物体的几何形状不能用欧几里得几何性质充分描述,但可以用一个称为分形维数的参数来表示。在这里,我们展示了一种特定的分形维数估计,即关联维数,它能够基于磁共振扩散成像数据描述人脑结构复杂性的变化。使用分形几何对示踪图表示的白质神经纤维束进行了几何复杂性分析。利用分形维数验证了众所周知的与年龄相关的白质组织变化。通过分形维数成功地观察和量化了大脑的结构变化,并与各向异性分数的变化进行了比较。