基于神经网络的舌组织图像处理与分类图形界面设计

I. Cantillo, A. González, Y. Martínez, I. Bueno, C. García, D. Bueno, V. H. Ortiz
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引用次数: 0

摘要

在这项工作中,我们介绍了一个基于ADALINE神经网络的不同组织检测和分类的图形界面,以舌头软组织为重点,为高精度诊断提供了工具。该界面能够识别受影响的区域,甚至通过探索同一样品的图像来识别正常和病理状况。自适应线性元素(ADALINE)神经网络成功地对95%的研究案例进行了正确分类,从70%的图像中进行验证,从总图像中提取30%用于训练,识别出健康或异常组织。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of a graphic interface for tongue tissue image processing and classification employing neural networks
In this work, we introduce a graphical interface for detection and classification of different tissue, focusing on tongue soft tissue, based on ADALINE neural networks to provide tools for a highly accurate diagnosis. The interface is capable to identify an affected area or even by exploration of an image of the same sample, to identify normal and pathological conditions. The Adaptive Linear Element (ADALINE) neural network successfully achieved a correct classification of 95% of total study cases, identifying either healthy or abnormal tissue, presented from a set of 70% of images for validations and 30% for training out of the total images.
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