视网膜神经节细胞的自动分类

R. M. Cesar, R. C. Coelho, L. da Fontoura Costa
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引用次数: 5

摘要

描述了利用二维形状分析和模式识别程序对神经细胞进行分类的实验。采用特征排序技术对猫视网膜神经节细胞(/spl α /和/spl β /细胞)的两种类型进行了形态学和特异性分析。形状特征包括分形维数、归一化多尺度弯曲能以及体细胞大小和树突化程度等标准度量。基于先验特征排序测试提供的信息,使用两个统计分类器(k近邻和最大似然)进行了多个分类实验。报告了令人鼓舞的认可结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic classification of retinal ganglion cells
Experiments on the classification of neural cells by means of 2D shape analysis and pattern recognition procedures are described. Two types of the cat's retinal ganglion cells (/spl alpha/ and /spl beta/ cells) are characterized by a set of morphological and specific features, which are analyzed by feature-ordering techniques. The shape features include the fractal dimension, the normalized multiscale bending energy as well as standard measures such as the size of the soma and of the dendritic arborization. Several classification experiments using two statistical classifiers (k-nearest neighbor and maximum likelihood) were carried out based on the information provided by the a priori feature-ordering tests. Encouraging recognition results are reported.
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