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Tramline and NP windows estimation for enhanced unsupervised retinal vessel segmentation

机译:增强无监督视网膜血管分割的电车曲线和NP窗口估计

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This paper presents a novel unsupervised vascular segmentation algorithm which is applied to retinal fundus images, however could be generalised to any two-dimensional vascular image. The algorithm presents a new fully automatic framework for vessel segmentation and comprises the following features: novel application of the NPWindows method for intensity distribution estimation on localised ‘image patches’; specialised treatment of small vessels by transformation to the one-dimensional domain to ensure enhanced detection; and excellent accuracy (93.42%) as compared with the recent active-contour based method by Al-Diri et al. [1] (92.58%) on the public DRIVE retinal image database [2].
机译:本文提出了一种新型无调节血管分割算法,其应用于视网膜眼底图像,然而可以推广到任何二维血管图像。 该算法为船只分割提供了一个新的全自动框架,包括以下特征:新颖的应用于本地化&#x2018的强度分布估计的npwindows方法;图像补丁&#x2019 ;; 通过转化到一维域的小血管的专用处理,以确保增强检测; 与最近的基于活性轮廓基于Al-DiRi等人的方法相比,优异的精度(93.42%)。 [1](92.58%)在公共驱动器视网膜图像数据库[2]。

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