骨化磁共振图像的分形维数作为大脑半球空间复杂性的度量

N. Maryenko, O. Stepanenko
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引用次数: 3

摘要

近几十年来,分形分析越来越多地应用于各个科学领域,包括神经科学;这种数学分析方法允许您量化所研究对象的空间填充程度及其空间配置复杂性的程度。该研究的目的是通过对颅骨磁共振脑图像的分形分析来确定大脑半球的分形维数。本研究使用了100名年龄在18-86岁(平均年龄41.72±1.58岁)的男女(56名女性,44名男性)相对健康(大脑无结构变化)的脑磁共振图像。研究了每个脑的5个断层切面。第1个冠状面断层位于颞叶最前方点的水平,第2个位于乳头体水平,第3个位于四叉肌板水平,第4个位于胼胝体脾水平。轴向断层位于丘脑水平。采用盒计数法对骨架化图像进行分形分析。所得数据采用普遍接受的统计方法进行处理。各层位分形维数的平均值、最小值和最大值分别为:冠状1层位- 1.207±0.003 (1.147÷1.277)、冠状2层位- 1.162±0.003 (1.077÷1.243)、冠状3层位- 1.156±0.003 (1.094÷1.224)、冠状4层位- 1.158±0.003 (1.109÷1.218)、轴向层位- 1.138±0.002 (1.079÷1.194)。5个层析切片的分形维数平均值为1.164±0.002 (1.126÷1.209), 4个冠状切片的分形维数平均值为1.171±0.002 (1.122÷1.219)。大脑半球骨架图像的分形分析可以量化大脑半球空间结构的拓扑特征和复杂性。分形维数的值可能受到所研究大脑区域的解剖特征、个体解剖特征以及导致大脑半球形状改变的萎缩和其他病理变化的影响。脑骨架图像的分形维数随年龄的增长呈下降趋势。冠状层析切片是表征年龄相关萎缩变化的最具代表性的切片。大脑半球骨架图像的分形分析可用于神经系统疾病的诊断,本研究结果可作为规范标准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fractal dimension of skeletonized MR images as a measure of cerebral hemispheres spatial complexity
In recent decades, fractal analysis has been increasingly used in various scientific fields, including neuroscience; this method of mathematical analysis allows you to quantify the space filling degree of the studied object and the degree of its spatial configuration complexity. The aim of the study was to determine the values of the fractal dimension of the cerebral hemispheres using fractal analysis of skeletonized magnetic resonance brain images. The present study used magnetic resonance brain images of 100 relatively healthy individuals (who had no structural changes in the brain) of both sexes (56 women, 44 men) aged 18-86 years (mean age 41.72±1.58 years). 5 tomographic sections of each brain were studied. The 1st coronal tomographic section was located at the level of the most anterior points of the temporal lobes, the 2nd – at the level of the mammillary bodies, the 3rd – at the level of the quadrigeminal plate, the 4th – at the level of the splenium of corpus callosum. The axial tomographic section was located at the level of the thalamus. Fractal analysis of skeletonized images was performed using box counting method. The obtained data were processed using generally accepted statistical methods. The average, minimum and maximum values of the fractal dimension of different tomographic sections were the following: 1st coronal section – 1.207±0.003 (1.147÷1.277), 2nd coronal section – 1.162±0.003 (1.077÷1.243), 3rd coronal section – 1.156±0.003 (1.094÷1.224), 4th coronal section – 1.158±0.003 (1.109÷1.218), axial section – 1.138±0.002 (1.079÷1.194). The average value of the fractal dimension of the five tomographic sections was 1.164±0.002 (1.126÷1.209), and the average value of the fractal dimension of the four coronal sections was 1.171±0.002 (1.122÷1.219). Fractal analysis of skeletonized images of the cerebral hemispheres allows to quantify the features of the topology and complexity of the spatial configuration of the cerebral hemispheres. The value of the fractal dimension can be influenced by the anatomical features of the studied areas of the brain, individual anatomical features, as well as atrophic and other pathological changes that lead to changes in the shape of the cerebral hemispheres. The values of the fractal dimension of skeletonized brain images tend to decrease with age. Coronal tomographic sections are the most representative for characterizing age-related atrophic changes. Fractal analysis of skeletonized images of the cerebral hemispheres can be used to diagnose diseases of the nervous system, and the results of the present study can be used as norm criteria.
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