Automated artery-vein classification in fundus color images

作者：Yang Yi; Bu Wei; Wang Kuanquan; Zheng Yalin; Wu Xiangqian^*

来源：2nd International Conference on Young Computer Scientists, Engineers and Educators, ICYCSEE 2016, 2016-08-20 to 2016-08-22.

DOI：10.1007/978-981-10-2053-7_21

• Adaptive histogram equalization
• Arteries and veins
• Automated methods
• Classification accuracy
• Diabetic retinopathy
• Disease surveillance
• Medical treatment
• Vessel classification

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.

• 出版日期2016
• 单位University of LIVERPOOL; The University of Liverpool