基于Frangi滤波和形态重建的视网膜血管分割

H. A. Nugroho, Rezty Amalia Aras, T. Lestari, I. Ardiyanto
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引用次数: 10

摘要

分析视网膜血管的结构变化是诊断和检测糖尿病视网膜病变、高血压、老年性黄斑变性(AMD)、动脉硬化等视网膜相关疾病的重要组成部分。提出了一种基于弗朗基滤波和形态学重构的视网膜眼底图像中视网膜血管分割方法。使用来自DRIVE和STARE数据集的彩色眼底图像对所提出的方法进行了评估。在DRIVE数据集中,该方法的灵敏度、特异度和准确度平均分别达到72.13%、96.65%和94.50%。同时,在STARE数据集中,平均灵敏度为75.50%,特异度为90.38%,准确率为88.76%。结果表明,该方法成功地分割了眼底图像中的视网膜血管。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Retinal vessel segmentation based on Frangi filter and morphological reconstruction
The analysis of structural changes in retinal vessels is the most important part for diagnosing and detecting retinal related diseases such as diabetic retinopathy, hypertension, age-related macular degeneration (AMD) and arteriosclerotic. This paper presents a method for segmenting retinal vessels in retinal fundus image based on Frangi filter and morphological reconstruction. The proposed method is evaluated using colour fundus images from DRIVE and STARE datasets. In DRIVE dataset, the performance of proposed method achieves an average of sensitivity, specificity and accuracy at 72.13%, 96.65 % and 94.50%, respectively. Meanwhile, in STARE dataset, it achieves an average sensitivity of 75.50%, specificity of 90.38% and accuracy of 88.76%. These results indicate that the proposed method successfully segments retinal vessels in fundus images.
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