Abstract:This review summarizes the applications and advancements of artificial intelligence (AI) in retinal vessel parameter analysis. Retinal vascular parameters, including vessel diameter, fractal dimension, vascular tortuosity, branching angles, and vessel density, are important indicators for assessing changes in the retinal vascular network structure. These parameters are not only related to various ophthalmic diseases but also reflect the conditions of systemic diseases such as diabetes and Alzheimer's disease. This article provides a detailed discussion on the advantages of AI technology in the automated identification and quantification of retinal vascular parameters, particularly in improving measurement efficiency and accuracy, and enabling the early detection and monitoring of various diseases. Additionally, the review addresses the challenges faced by AI in the analysis of retinal vascular parameters, such as data standardization and insufficient sample diversity, and proposes directions for future research. By thoroughly analyzing the application of AI in retinal vascular parameter analysis, this article aims to offer new perspectives and methods for clinical diagnosis and early intervention of diseases, holding significant clinical importance and application prospects. Key word:artificial intelligence;retinal vessels;retinal vascular parameters
