基于舌象分析的ii型糖尿病预后工具的开发

A. Vijayalakshmi, M. Shahaana, N. Nivetha, K. Subramaniam
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引用次数: 5

摘要

舌头图像分析是一种识别人体内部器官(即胰腺)状况的方法。由于主观的、定性的和实验的分析,存在一定的局限性。糖尿病患者的舌头中央可能有一层灰色的涂层。因此,舌头图像的异常显示了病情(即,该人是否患有糖尿病)。在此基础上,提出了一种计算机化的图像分析方法,以提高分类效率。同样,使用MATLAB对几何、颜色和纹理三个定量特征进行测量,然后使用SVM分类器和CNN对数据集中的图像进行分类,并比较两种方法的分类结果。在预测精度上,CNN优于SVM。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of Prognosis Tool for Type-II Diabetics using Tongue Image Analysis
Tongue image analysis is a method to identify the conditions of internal organs of the human body (i.e., pancreas). It has certain limitations due to subjective, qualitative and experimental analysis. A person with diabetics can have a grey colour coating at the center of the tongue. Thus the abnormalities of tongue images exhibit the condition (i.e., whether the person is diabetic or not). Based on that, this paper represent a computerised image analysis to improve the efficiency of the classification. Likewise, the three quantitative features like geometry, colour and texture are measured using MATLAB, then the SVM classifier and CNN are used for the classification images from the dataset and the results of both methods are compared. Based on the accuracy of prediction CNN has better results than SVM.
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