A Fundus Image Dataset for AI-based Artery-Vein Vessel Segmentation

Abstract

Retinal artery-vein vessels are associated with systemic chronic diseases and cardiovascular diseases. Therefore, the accurate quantitative analysis of retinal artery-vein vessels is the preliminary basis of clinical diagnosis. Most of the existing artificial intelligence(AI) methods are data-driven. Although some public retinal artery-vein vessel segmentation datasets have been released, their data quality is unsatisfactory. In this paper, we establish a new fundus image dataset for AI-based artery-vein segmentation, Fundus-AVSeg. It consists of 100 high-resolution fundus images with pixel-wise manual annotation by professional ophthalmologists. We believe our Fundus-AVSeg will benefit the further development of retinal artery-vein vessel segmentation.