Lazar Istvan, Hajdu Andras
University of Debrecen, Department of Informatics, Hungary.
Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:1458-61. doi: 10.1109/EMBC.2012.6346215.
In this paper we present a fast and simple, yet accurate method for the segmentation of retinal blood vessels. Many diseases of the eye result in the distortions of the vessels. The precise location of the major optic veins may be used for the localization of other anatomical parts, such as the macula and the optic disc. Also, many microaneurysm detection methods consider an additional vessel segmentation step. The proposed method realizes the recognition of vessels through considering cross-sections of the image at different orientations. Peaks on the profiles are localized and their heights are measured. This way, a set of height values are assigned to every pixel of the image. Simple statistics are calculated for every pixel, and combined to construct a vessel score map. We apply a simple thresholding procedure and postprocessing step to obtain a binary vessel mask. The method has been tested on the publicly available DRIVE database, and it proved to be competitive with the state-of-the-art.
在本文中，我们提出了一种快速、简单且准确的视网膜血管分割方法。许多眼部疾病会导致血管变形。主要视神经静脉的精确位置可用于定位其他解剖部位，如黄斑和视盘。此外，许多微动脉瘤检测方法都将血管分割作为一个额外步骤。所提出的方法通过考虑图像在不同方向上的横截面来实现血管识别。定位轮廓上的峰值并测量其高度。这样，为图像的每个像素分配一组高度值。对每个像素计算简单的统计量，并将其组合以构建血管得分图。我们应用一个简单的阈值处理程序和后处理步骤来获得二进制血管掩码。该方法已在公开可用的DRIVE数据库上进行了测试，并且被证明与当前最先进的方法具有竞争力。
