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首页> 外文期刊>International Journal of Swarm Intelligence and Evolutionary Computation >Analysis of Vasculature Detection in Human Retinal Images Using Bacterial Foraging Optimization Based Multi Thresholding
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Analysis of Vasculature Detection in Human Retinal Images Using Bacterial Foraging Optimization Based Multi Thresholding

机译：基于多阈值的细菌觅食优化分析人类视网膜图像中的脉管系统。

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摘要

Analysis of blood vessels in digital retinal fundus images is an important problem attempted in contemporary biomedical engineering research. In this work, normal and abnormal retinal images are pre-processed with adaptive histogram equalization and fuzzy filtering. Pre-processed images are then subjected to Tsallis multi-level thresholding method. The threshold levels determined by the chosen method are further optimized using bacterial foraging optimization techniques in order to improve the vessel content. The obtained results are validated using similarity measures by comparing with the corresponding ground truth of each image. Statistical and Tamura features are derived from optimal multi-level thresholding output images to analyse the healthy and pathological images. Results demonstrate that attempted series of pre-processing techniques enhances the edge information considerably and improves the efficacy of segmentation. It is observed that bacterial foraging optimization for Tsallis multi-level thresholding is able to extract retinal vasculature. Similarity measures show that this method provides considerable improvement in the extraction of vessel edges. Further, the statistical and Tamura features derived from detected vessels provide better differentiation between healthy and pathological images. As presence and absence of vessels in retina are clinically significant, the findings seem to be useful.
机译：数字视网膜眼底图像中的血管分析是当代生物医学工程研究中尝试的重要问题。在这项工作中，通过自适应直方图均衡和模糊滤波对正常和异常的视网膜图像进行预处理。然后对预处理的图像进行Tsallis多级阈值化方法。使用细菌觅食优化技术进一步优化通过所选方法确定的阈值水平，以提高容器含量。通过与每个图像的相应地面真实情况进行比较，使用相似性度量来验证所获得的结果。统计和Tamura特征来自最优的多级阈值输出图像，以分析健康和病理图像。结果表明，尝试的一系列预处理技术可以显着增强边缘信息并提高分割效果。观察到针对Tsallis多级阈值化的细菌觅食优化能够提取视网膜脉管系统。相似性度量表明，该方法在提取血管边缘方面提供了可观的改进。此外，从检测到的血管中获得的统计特征和Tamura特征可更好地区分健康图像和病理图像。由于视网膜中血管的存在与否在临床上具有重要意义，因此该发现似乎是有用的。

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