基于视网膜眼底图像分形和不变矩分析的眼部疾病分类

Noah Hutson, Anik Karan, J. Adkinson, P. Sidiropoulos, I. Vlachos, L. Iasemidis
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引用次数: 4

摘要

人眼图像分析为眼部疾病提供了新的见解,并有可能协助其自动诊断。本文采用图像分形分析、图像不变矩分析和线性判别分析(LDA)对a)健康受试者和b)糖尿病视网膜病变或c)青光眼患者处理后的眼底(视网膜)图像进行分类分析。利用分形维数和Hu不变矩,LDA在三种情况下的分类准确率达到99.2%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Classification of Ocular Disorders Based on Fractal and Invariant Moment Analysis of Retinal Fundus Images
Image analysis of the human eye has provided new insight into ocular disorders and has the potential to assist in their automated diagnosis. We herein report results from analysis of the processed fundus (retina) images from a) healthy subjects and patients diagnosed with b) diabetic retinopathy or c) glaucoma, by means of image fractal analysis and image invariant moments, and linear discriminant analysis (LDA) for classification. Using the fractal dimension and Hu's invariant moments, LDA achieved classification accuracy of 99.2% for the three conditions.
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