Artery/vein classification using reflection features in retina fundus images

作者：Huang, Fan; Dashtbozorg, Behdad; Romeny, Bart M. ter Haar^*

来源：Machine Vision and Applications, 2018, 29(1): 23-34.

DOI：10.1007/s00138-017-0867-x

• Artery/vein classification
• Blood vessels
• Retinal image
• Feature extraction

Automatic artery/vein (A/V) classification is one of the important topics in retinal image analysis. It allows the researchers to investigate the association between biomarkers and disease progression on a huge amount of data for arteries and veins separately. Recent proposed methods, which employ contextual information of vessels to achieve better A/V classification accuracy, still rely on the performance of pixel-wise classification, which has received limited attention in recent years. In this paper, we show that these classification methods can be markedly improved. We propose a new normalization technique for extracting four new features which are associated with the lightness reflection of vessels. The accuracy of a linear discriminate analysis classifier is used to validate these features. Accuracy rates of 85.1, 86.9 and 90.6% were obtained on three datasets using only local information. Based on the introduced features, the advanced graph-based methods will achieve a better performance on A/V classification.

• 出版日期2018-1
• 单位东北大学