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首页> 外文期刊>Biocybernetics and biomedical engineering >Automatic parameters selection of Gabor filters with the imperialism competitive algorithm with application to retinal vessel segmentation
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Automatic parameters selection of Gabor filters with the imperialism competitive algorithm with application to retinal vessel segmentation

机译:基于帝国主义竞争算法的Gabor滤光片自动参数选择及其在视网膜血管分割中的应用

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摘要

Retinal images play an important role in the early diagnosis of diseases such as diabetes. In the present study, an automatic image processing technique is proposed to segment retinal blood vessels in fundus images. The technique includes the design of a bank of 180 Gabor filters with varying scale and elongation parameters. Furthermore, an optimization method, namely, the imperialism competitive algorithm (ICA), is adopted for automatic parameter selection of the Gabor filter. In addition, a systematic method is proposed to determine the threshold value for reliable performance. Finally, the performance of the proposed approach is analyzed and compared with that of other approaches on the basis of the publicly available DRIVE database. The proposed method achieves an area under the receiver operating characteristic curve of 0.953 and an average accuracy of up to 0.9392. Thus, the results show that the proposed method is well comparable with alternative methods in the literature. (C) 2017 Nalecz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences. Published by Elsevier B.V. All rights reserved.
机译:视网膜图像在糖尿病等疾病的早期诊断中起着重要作用。在本研究中,提出了一种自动图像处理技术来分割眼底图像中的视网膜血管。该技术包括设计一组 180 个具有不同比例和伸长率参数的 Gabor 滤波器。此外,还采用了一种优化方法,即帝国主义竞争算法(ICA)对Gabor滤波器进行自动参数选择。此外,还提出了一种系统的方法,用于确定可靠性能的阈值。最后,在公开的DRIVE数据库的基础上,对所提方法的性能进行了分析,并与其他方法进行了比较。所提方法的受试者工作特征曲线下面积为0.953,平均精度高达0.9392。结果表明,所提方法与文献中的替代方法具有较好的可比性。(C) 2017 波兰科学院 Nalecz 生物控制论和生物医学工程研究所。由以下开发商制作:Elsevier B.V.保留所有权利。

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