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Fully automatic algorithm for the analysis of vessels in the angiographic image of the eye fundus

机译:全自动分析眼底血管造影图像中的血管的算法

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Background The available scientific literature contains descriptions of manual, semi-automated and automated methods for analysing angiographic images. The presented algorithms segment vessels calculating their tortuosity or number in a given area. We describe a statistical analysis of the inclination of the vessels in the fundus as related to their distance from the center of the optic disc. Methods The paper presents an automated method for analysing vessels which are found in angiographic images of the eye using a Matlab implemented algorithm. It performs filtration and convolution operations with suggested masks. The result is an image containing information on the location of vessels and their inclination angle in relation to the center of the optic disc. This is a new approach to the analysis of vessels whose usefulness has been confirmed in the diagnosis of hypertension. Results The proposed algorithm analyzed and processed the images of the eye fundus using a classifier in the form of decision trees. It enabled the proper classification of healthy patients and those with hypertension. The result is a very good separation of healthy subjects from the hypertensive ones: sensitivity - 83%, specificity - 100%, accuracy - 96%. This confirms a practical usefulness of the proposed method. Conclusions This paper presents an algorithm for the automatic analysis of morphological parameters of the fundus vessels. Such an analysis is performed during fluorescein angiography of the eye. The presented algorithm automatically calculates the global statistical features connected with both tortuosity of vessels and their total area or their number.
机译:背景技术可用的科学文献包含用于分析血管造影图像的手动,半自动和自动方法的描述。提出的算法对船只进行曲折计算,以计算其在给定区域内的曲折度或数量。我们描述了眼底血管倾斜度的统计分析,这与它们距视盘中心的距离有关。方法本文介绍了一种自动方法,该方法使用Matlab实现的算法分析在眼睛的血管造影图像中发现的血管。它使用建议的掩码执行过滤和卷积操作。结果是包含关于血管位置及其相对于视盘中心的倾斜角度的信息的图像。这是一种分析血管的新方法,其有用性已在高血压诊断中得到证实。结果所提出的算法使用决策树形式的分类器对眼底图像进行分析和处理。它可以对健康患者和高血压患者进行正确分类。结果是将健康受试者与高血压受试者很好地分开:敏感性-83%,特异性-100%,准确性-96%。这证实了所提出的方法的实际实用性。结论本文提出了一种自动分析眼底血管形态参数的算法。这种分析是在眼睛的荧光素血管造影期间进行的。提出的算法自动计算与船只的曲折度及其总面积或数量有关的全局统计特征。

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