Jebaseeli T Jemima, Durai C Anand Deva, Peter J Dinesh
Department of Computer Science and Engineering, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, India.
Department of Computer Science and Engineering, King Khalid University, Abha, Saudi Arabia.
J Med Phys. 2019 Jan-Mar;44(1):21-26. doi: 10.4103/jmp.JMP_51_18.
Accurate segmentation of retinal blood vessel is an important task in computer-aided diagnosis and surgery planning of diabetic retinopathy. Despite the high-resolution of photographs in fundus photography, the contrast between the blood vessels and the retinal background tends to be poor.
In this proposed method, contrast-limited adaptive histogram equalization is used for noise cancellation and improving the local contrast of the image. By uniform distribution of gray values, it enhances the image and makes the hidden features more visible. The extraction of the retinal blood vessel depends on two levels of optimization. The first level is the extraction of blood vessels from the retinal image using Kirsch's templates. The second level is used to find the coarse vessels with the assistance of the unsupervised method of Fuzzy C-Means clustering. After segmentation, to remove the optic disc, the region-based active contour method is used. The proposed system is evaluated using DRIVE dataset with 40 images.
The performance of the proposed approach is comparable with state of the art techniques. The proposed technique outperforms the existing techniques by achieving an accuracy of 99.55%, sensitivity of 71.83%, and specificity of 99.86% in the experimental setup.
The results show that this approach is a suitable alternative technique for the supervised method and it is support for similar fundus images dataset.
准确分割视网膜血管是糖尿病视网膜病变计算机辅助诊断和手术规划中的一项重要任务。尽管眼底摄影照片具有高分辨率，但血管与视网膜背景之间的对比度往往较差。
在本提出的方法中，使用对比度受限自适应直方图均衡化来消除噪声并改善图像的局部对比度。通过灰度值的均匀分布，它增强了图像并使隐藏特征更明显。视网膜血管的提取依赖于两个优化级别。第一级是使用基尔希模板从视网膜图像中提取血管。第二级用于在模糊C均值聚类的无监督方法辅助下找到粗血管。分割后，使用基于区域的主动轮廓方法去除视盘。使用包含40张图像的DRIVE数据集对所提出的系统进行评估。
所提出方法的性能与现有技术相当。在所提出的技术在实验设置中实现了99.55%的准确率、71.83%的灵敏度和99.86%的特异性，优于现有技术。
结果表明，该方法是监督方法的一种合适替代技术，并且适用于类似的眼底图像数据集。
