Automated Artery-Vein Classification in Fundus Color Images

• 作者: Kuanquan Wang Wei Bu Xiangqian Wu Yalin Zheng Yi Yang
• 来源期刊: 国际计算机前沿大会会议论文集
• 学科: 社会科学
• 关键词: Diabetic RETINOPATHY Vessel classification ARTERIES and VEINS Feature extraction Support vector machines Adaptive HISTOGRAM EQUALIZATION
• 年，卷（期）: 2016,（1）
• 页码范围: 59-61
• 页数: 3页
• 分类号: C5

摘要

The estimation of Arterio-Venous ratio (AVR) is an important phase in diagnosing various vascular diseases e.g. Diabetic Retinopathy. For calculating this value, it is essential to differentiate the vessels into arteries and veins. This paper presents a novel structural and automated method for artery/vein vessels classification in retinal images. Our method is tested on DRIVE database and the classification accuracy is 88.7 % for pixels and 89.07 % for vessel lines, respectively, which demonstrate the effectives of our approach. Our method will help to achieve the fundus disease surveillance on mobile and remote medical treatment. It has a remarkable social significance.