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An application of Bottom Hat transformation to extract blood vessel from retinal images

机译:Bottom Hat变换在视网膜图像中提取血管的应用

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Extraction of blood vessels in retinal images provides early diagnosis of different retinopathy diseases (diabetic retinopathy, injury detection, abnormality detection, hemorrhage detection and macular degeneration). This paper presents about the problem of noises and also the blood vessels appearing darker and tiny in the retinal images. This paper introduces a new method for the extraction of retinal blood vessels in retinal fundus images which will be useful to eye specialists in their visual examination of retina and will definitely improve automatic retinal images analysis. In this paper, at first, light reflectance removal technique is used to remove the brighter strips of the images by using green plane of the image. Then, salt and pepper noise and Gaussian noise of the image is removed using median filter and Gaussian filter respectively. After that morphological Bottom Hat Transform is applied to extract the blood vessels. Finally, blood vessels are enhanced using sharpening technique with an unsharp masking. Results are compared with different blood vessel detection algorithms and are found to be encouraging.
机译:视网膜图像中血管的提取可对各种视网膜病变疾病(糖尿病性视网膜病变,损伤检测,异常检测,出血检测和黄斑变性)进行早期诊断。本文介绍了噪声的问题,以及视网膜图像中血管显得更暗,更细。本文介绍了一种提取眼底图像中视网膜血管的新方法,该方法将对眼科专家进行视网膜视觉检查很有用,并且肯定会改善视网膜图像的自动分析。在本文中,首先,使用光反射去除技术通过使用图像的绿色平面来去除图像的亮条。然后,分别使用中值滤波器和高斯滤波器去除图像的盐和胡椒噪声和高斯噪声。之后,应用形态学的Bottom Hat Transform提取血管。最后,使用锐化技术和不清晰的遮罩增强血管。将结果与不同的血管检测算法进行比较,发现结果令人鼓舞。

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