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人脑小脑分形维数的比较分析:图像预处理和分形分析方法的影响。

COMPARATIVE ANALYSIS OF FRACTAL DIMENSIONS OF HUMAN CEREBELLUM: IMPACT OF IMAGE PREPROCESSING AND FRACTAL ANALYSIS METHODS.

机构信息

KHARKIV NATIONAL MEDICAL UNIVERSITY, KHARKIV, UKRAINE.

出版信息

Wiad Lek. 2022;75(2):438-443.

Abstract

OBJECTIVE

The aim: To compare the values of the fractal dimensions of human cerebellum obtained using different algorithms of image preprocessing and different methods of fractal analysis.

PATIENTS AND METHODS

Materials and methods: The study involved 120 people without structural changes in the brain (age 18-86 years, 55 men and 65 women). T1- and T2-weighted MR brain images were studied. Fractal analysis was performed using box counting and pixel dilatation methods. Fractal dimensions of cerebellar tissue as a whole, cerebellar cortex and its individual layers, cerebellar white matter were measured and compared to each other and to fractal dimension of cerebellar white matter determined in cadaveric cerebella.

RESULTS

Results: It was no significant difference between fractal dimension values of cerebellar tissue as a whole measured on T1 and T2 weighted magnetic resonance images of cerebellum, and fractal dimension values measured on the same images using different methods of fractal analysis - pixel dilatation and box counting. T2 weighted images are preferable for fractal analysis of different components of cerebellar tissue. Segmentation according to pixel luminance is the preferable image preprocessing method for fractal analysis of cerebellar cortex as a whole, individual cortical layers and cerebellar tissue as a whole; skeletonizing of cerebellar magnetic resonance images is the preferable method of the image preprocessing for fractal analysis of cerebellar white matter.

CONCLUSION

Conclusions: The algorithm of image preprocessing, magnetic resonance imaging sequence and method of fractal analysis should be chosen according to aim of quantitative study of cerebellar magnetic resonance images and features of the studied structure of cerebellum.

摘要

目的

比较使用不同图像预处理算法和不同分形分析方法获得的人脑小脑分形维数的价值。

材料和方法

本研究纳入了 120 名无脑结构改变的人(年龄 18-86 岁,55 名男性和 65 名女性)。研究了 T1 和 T2 加权磁共振脑图像。使用盒计数和像素扩张方法进行分形分析。测量并比较了小脑组织、小脑皮质及其各层、小脑白质的分形维数,并与尸体小脑确定的小脑白质分形维数进行比较。

结果

小脑组织整体的分形维数在 T1 和 T2 加权磁共振小脑图像上测量值之间无显著差异,使用不同分形分析方法——像素扩张和盒计数在同一图像上测量值之间也无显著差异。T2 加权图像更适合小脑组织不同成分的分形分析。根据像素亮度进行分割是小脑皮质整体、各皮质层和小脑组织整体分形分析的首选图像预处理方法;小脑磁共振图像的骨架化是小脑白质分形分析的首选图像预处理方法。

结论

应根据定量研究小脑磁共振图像的目的和小脑研究结构的特点选择图像预处理算法、磁共振成像序列和分形分析方法。

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