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首页> 外文期刊>International Journal of Applied Engineering Research >Analysis of Human Retinal Images for Retinoblastoma using White Top Hat Transform
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Analysis of Human Retinal Images for Retinoblastoma using White Top Hat Transform

机译：使用白色顶部帽子变换的视网膜母细胞瘤人的视网膜图像分析

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摘要

Recent day's biomedical image analysis has a strong custom of developing image analysis techniques that show potential for high effect in clinical practice for diagnosing. Automated analysis of retinal images is a challenging research area that aims to provide automated methods in setting up medical system that can monitor a large number of people for sight threatening diseases likely Retinoblastoma and Diabetic Retinopathy to help in the early detection. The most common degradations indetection of retinal images is their poor contrast quality and noise. The gray scale retina image feature analysis by segmentation are inappropriate for diagnosing the pathologies in retinal images since it needs to be analyzed in terms of color, texture and luminance. In this paper, a new approach based on morphological White Top-Hat Transform is carried out on retinal images to enhance the contrast and quality. The White Top-Hat Transform is used to enhance brighter region in a dark background by suppress large regions and keeping the small size features to detect the pathologies part. The results indicate that proposed method improves the contrast of medical images and can help with better diagnosis.
机译：近期的生物医学图像分析具有开发图像分析技术的强烈习惯，表明在诊断临床实践中显示出高效果的潜力。视网膜图像的自动分析是一个具有挑战性的研究领域，旨在提供自动化方法，在建立医疗系统时，可以监测大量人的视力威胁性疾病可能的视网膜母细胞瘤和糖尿病视网膜病变，以帮助早期发现。视网膜图像的最常见的降解是它们较差的对比度和噪音。通过分割的灰度视网膜图像特征分析不适合诊断视网膜图像中的病理学，因为它需要在颜色，纹理和亮度方面进行分析。本文在视网膜图像上进行了一种基于形态白色顶帽变换的新方法，以提高对比度和质量。白色顶帽变换用于通过抑制大区域并保持小尺寸特征来增强暗背景中的更亮的区域以检测病理部件。结果表明，提出的方法改善了医学图像的对比度，可以帮助更好地诊断。

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