视网膜图像视盘的水平集分割

Chuang Wang, Djibril Kaba, Yongmin Li
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引用次数: 34

摘要

视网膜图像的分析可以为视网膜和血管疾病的检测和追踪提供重要信息。本文的目的是设计一种在数字眼底图像中自动分割视盘的方法。采用模板匹配法对视盘中心进行近似定位,提取血管对视盘中心进行复位。然后应用结合边缘项、距离正则化项和形状先验项的水平集方法对视盘形状进行分割。七个指标被用来评价方法的性能。在三个公共数据集DRIVE、DIARETDB1和DIARETDB0上对该方法的有效性进行了评估。结果表明,我们的方法在这些数据集上优于最先进的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Level Set Segmentation of Optic Discs from Retinal Images
Analysis of retinal images can provide important information for detecting and tracing retinal and vascular diseases. The purpose of this work is to design a method that can automatically segment the optic disc in the digital fundus images. The template matching method is used to approximately locate the optic disc centre, and the blood vessel is extracted to reset the centre. This is followed by applying the Level Set Method, which incorporates edge term, distance-regularization term and shape-prior term, to segment the shape of the optic disc. Seven measures are used to evaluate the performance of the methods. The effectiveness of the proposed method is evaluated against alternative methods on three public data sets DRIVE, DIARETDB1 and DIARETDB0. The results show that our method outperforms the state-of-the-art methods on these datasets.
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