智能技术学报

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稿件标题: Retinal Image Segmentation Using Double-Scale Nonlinear Thresholding on Vessel Support Regions
稿件作者: Qingyong Li, Min Zheng, Feng Li, Jianzhu Wang, Yangli-ao Geng, Haibo Jiang
关键字词: retinal vessel segmentation; double-scale filtering; adaptive local thresholding; vessel support regions
文章摘要: Retinal vessel segmentation is a critical indicator of diagnosis, screening, and treatment of cardiovascular and ophthalmologic diseases. Due to the fact that the retinal vessels usually have some tiny structures and blurred boundaries, especially with remarkable noises, it is difficult to correctly segment the vascular. In this paper, we propose a novel Double-scale Nonlinear Thresholding (DNT) method based on vessel support regions. Firstly, the Double-Scale Filtering (DSF) method is applied to enhance the contrast between the foreground vascular and the background stuffs. Secondly, we segment the fine and coarse vessels by corresponding Adaptive Local Thresholding (ALT) and Fixed-Ratio Thresholding (FRT) method. Finally, we obtain the binary segmentation by fusion of fine and coarse vessels. Experiments are conducted on the publicly available DRIVE and STARE datasets, which show the effectiveness of the proposed method on retinal vessel segmentation.
收录刊物: 2017年2卷3期
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