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Measurement of retinal vessel widths from fundus images based on 2-D modeling

机译:基于二维建模的眼底图像测量视网膜血管宽度

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摘要

Changes in retinal vessel diameter are an important sign of diseases such as hypertension, arteriosclerosis and diabetes mellitus. Obtaining precise measurements of vascular widths is a critical and demanding process in automated retinal image analysis as the typical vessel is only a few pixels wide. This paper presents an algorithm to measure the vessel diameter to subpixel accuracy. The diameter measurement is based on a two-dimensional difference of Gaussian model, which is optimized to fit a two-dimensional intensity vessel segment. The performance of the method is evaluated against Brinchmann-Hansen's half height, Gregson's rectangular profile and Zhou's Gaussian model. Results from 100 sample profiles show that the presented algorithm is over 30% more precise than the compared techniques and is accurate to a third of a pixel.
机译:视网膜血管直径的变化是诸如高血压,动脉硬化和糖尿病等疾病的重要标志。由于典型的血管只有几像素宽,因此获得精确的血管宽度测量值是自动化视网膜图像分析中的一项至关重要的工作。本文提出了一种测量血管直径至亚像素精度的算法。直径测量基于高斯模型的二维差异,该差异经过优化以适合二维强度血管段。针对Brinchmann-Hansen的半高,Gregson的矩形轮廓和Zhou的高斯模型对方法的性能进行了评估。来自100个样本配置文件的结果表明,与所比较的技术相比,该算法的精度提高了30%以上,并且精确到像素的三分之一。

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