Development of Technology for the Identification of Model Parameters for Dendritic Structures Images

R. Paringer, M. Boori, Y. Donon, A. Kupriyanov, D. Kirsh, Kravtsova Natalia
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Abstract

This work aims to increase the reliability of dendritic crystallogram’s images classification. Crystallographic methods are used for medical diagnosis and we propose here to improve the reliability of their classification through an improved description of de dendritic structures’ features. In this paper, we use the parameters of the mathematical model describing objects with dendritic structure. We developed a technology of parameters identification from a model image of dendritic structures, that was then implemented through the use of geometric and statistical features, together with a nearest neighbor classification algorithm.
树突结构图像模型参数识别技术的发展
本工作旨在提高树突晶体图图像分类的可靠性。晶体学方法用于医学诊断,我们建议通过改进枝晶结构特征的描述来提高其分类的可靠性。在本文中,我们使用数学模型的参数来描述具有树枝状结构的物体。我们开发了一种从树突结构模型图像中识别参数的技术,然后通过使用几何和统计特征以及最近邻分类算法来实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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