Robust vessel segmentation in fundus images.
Robust vessel segmentation in fundus images.
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DOI：
10.1155/2013/154860
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发表时间：
2013
影响因子：
7.6
通讯作者：
Michelson G
中科院分区：
文献类型：
--
作者：
Budai A;Bock R;Maier A;Hornegger J;Michelson G
眼底照片是检查人眼最常用的方法之一。眼底照片的评价是由医学专家在耗时的目视检查中进行的。我们的目标是利用计算机辅助诊断加速这一过程。作为第一步，有必要对图像中的结构进行分割以进行组织分化。由于眼睛是唯一的器官，在那里血管系统可以在体内和非介入的方式成像，而不使用昂贵的扫描仪，血管树是最有趣的和重要的结构分析之一。眼底图像的质量和分辨率正在迅速提高。因此，分割方法需要适应高分辨率的新挑战。在本文中，我们提出了一种与原有的Frangi方法相比，减少计算时间，达到较高的精度和提高灵敏度的方法。这种方法包含避免潜在问题的方法，如厚血管的镜面反射。使用STARE和DRIVE数据库对所提出的方法进行了评估，并提出了一个新的高分辨率眼底数据库，将其与最先进的算法进行比较。结果表明，平均准确率在94%以上，计算需求低。这比最先进的方法要好。
One of the most common modalities to examine the human eye is the eye-fundus photograph. The evaluation of fundus photographs is carried out by medical experts during time-consuming visual inspection. Our aim is to accelerate this process using computer aided diagnosis. As a first step, it is necessary to segment structures in the images for tissue differentiation. As the eye is the only organ, where the vasculature can be imaged in an in vivo and noninterventional way without using expensive scanners, the vessel tree is one of the most interesting and important structures to analyze. The quality and resolution of fundus images are rapidly increasing. Thus, segmentation methods need to be adapted to the new challenges of high resolutions. In this paper, we present a method to reduce calculation time, achieve high accuracy, and increase sensitivity compared to the original Frangi method. This method contains approaches to avoid potential problems like specular reflexes of thick vessels. The proposed method is evaluated using the STARE and DRIVE databases and we propose a new high resolution fundus database to compare it to the state-of-the-art algorithms. The results show an average accuracy above 94% and low computational needs. This outperforms state-of-the-art methods.