首页> 外文期刊>International journal of healthcare information systems and informatics : >Automatic Detection of Blood Vessel in Retinal Images Using Vesselness Enhancement Filter and Adaptive Thresholding
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Automatic Detection of Blood Vessel in Retinal Images Using Vesselness Enhancement Filter and Adaptive Thresholding

机译:使用血管增强滤波器和自适应阈值自动检测视网膜图像中的血管

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摘要

Retinal blood vessels detection and measurement of morphological attributes, such as length, width, sinuosity and corners are very much important for the diagnosis and treatment of different ocular diseases including diabetic retinopathy (DR), glaucoma, and hypertension. This paper presents a integration method for blood vessels detection in fundus retinal images. The proposed method consists of two main steps. The first step is pre-processing of retinal image to improve the retinal images by evaluation of several image enhancement techniques. The second step is vessels detection, the vesselness filter is usually used to enhance the blood vessels. The enhancement filter is designed from the adaptive thresholding of the output of the vesselness filter for vessels detection. The algorithms performance is compared and analyzed on three publicly available databases (DRIVE, STARE and CHASE_DB) of retinal images using a number of measures, which include accuracy, sensitivity, and specificity.
机译:视网膜血管检测和测量形态学属性,例如长度,宽度,塞子和角落对不同眼部疾病的诊断和治疗具有非常重要的是,包括糖尿病视网膜病变(DR),青光眼和高血压。本文介绍了眼底视网膜图像中血管检测的一体化方法。该方法包括两个主要步骤。第一步是通过评估若干图像增强技术来改善视网膜图像的预处理。第二步骤是血管检测,血管过滤器通常用于增强血管。增强滤波器由用于血管检测的血管滤波器的输出的自适应阈值化设计。使用多种措施对算法进行比较和分析视网膜图像的三个公共数据库(驱动器,凝视,Chase_DB),包括准确性,灵敏度和特异性。

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