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二维神经元图像的盒计数法:方法改进及在猴脑和人脑图像上的定量分析

Box-Counting Method of 2D Neuronal Image: Method Modification and Quantitative Analysis Demonstrated on Images from the Monkey and Human Brain.

作者信息

Rajković Nemanja, Krstonošić Bojana, Milošević Nebojša

机构信息

Department of Biophysics, School of Medicine, University of Belgrade, Višegradska 26/2, 11000 Belgrade, Serbia.

Department of Anatomy, School of Medicine, University of Novi Sad, Hajduk Veljkova 21, 21000 Novi Sad, Serbia.

出版信息

Comput Math Methods Med. 2017;2017:8967902. doi: 10.1155/2017/8967902. Epub 2017 May 8.

Abstract

This study calls attention to the difference between traditional box-counting method and its modification. The appropriate scaling factor, influence on image size and resolution, and image rotation, as well as different image presentation, are showed on the sample of asymmetrical neurons from the monkey dentate nucleus. The standard BC method and its modification were evaluated on the sample of 2D neuronal images from the human neostriatum. In addition, three box dimensions (which estimate the space-filling property, the shape, complexity, and the irregularity of dendritic tree) were used to evaluate differences in the morphology of type III aspiny neurons between two parts of the neostriatum.

摘要

本研究提请注意传统盒计数法与其改进方法之间的差异。在来自猴齿状核的不对称神经元样本上展示了适当的缩放因子、对图像大小和分辨率的影响、图像旋转以及不同的图像呈现方式。在来自人类新纹状体的二维神经元图像样本上评估了标准盒计数法及其改进方法。此外,使用三个盒维度(用于估计树突状树的空间填充特性、形状、复杂性和不规则性)来评估新纹状体两部分之间III型无棘神经元形态的差异。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94fe/5439180/a3521f533913/CMMM2017-8967902.001.jpg

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