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首页> 外文期刊>Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice >Automatic detection and characterisation of retinal vessel tree bifurcations and crossovers in eye fundus images.
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Automatic detection and characterisation of retinal vessel tree bifurcations and crossovers in eye fundus images.

机译：眼底图像中视网膜血管树分叉和交叉的自动检测和表征。

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摘要

Analysis of retinal vessel tree characteristics is an important task in medical diagnosis, specially in cases of diseases like vessel occlusion, hypertension or diabetes. The detection and classification of feature points in the arteriovenous eye tree will increase the information about the structure allowing its use for medical diagnosis. In this work a method for detection and classification of retinal vessel tree feature points is presented. The method applies and combines imaging techniques such as filters or morphologic operations to obtain an adequate structure for the detection. Classification is performed by analysing the feature points environment. Detection and classification of feature points is validated using the VARIA database. Experimental results are compared to previous approaches showing a much higher specificity in the characterisation of feature points while slightly increasing the sensitivity. These results provide a more reliable methodology for retinal structure analysis.
机译：视网膜血管树特征的分析是医学诊断中的重要任务，特别是在诸如血管闭塞，高血压或糖尿病等疾病的情况下。动静脉眼树中特征点的检测和分类将增加有关该结构的信息，从而使其可用于医学诊断。在这项工作中，提出了一种检测和分类视网膜血管树特征点的方法。该方法应用并结合了诸如过滤器或形态学操作之类的成像技术，以获得用于检测的适当结构。通过分析特征点环境进行分类。使用VARIA数据库验证特征点的检测和分类。将实验结果与以前的方法进行比较，结果表明特征点的表征具有更高的特异性，同时灵敏度略有提高。这些结果为视网膜结构分析提供了更可靠的方法。

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