In this study, we summarize the advancements in high-resolution vascular imaging technology and its applications in the biomedical field. In particular, we focus on quantitative characterization methods applicable to high-resolution vascular images. The quantification process of vascular images generally comprises three main steps: image preprocessing, vascular image reconstruction and quantitative characterization acquisition, and statistical analysis of quantitative parameters. We provide a detailed explanation of the algorithm pipeline, accuracy assessment, and potential optimization directions for the methods employed in each step. Furthermore, we explore the significance of extracting biological information from various vascular and blood parameters for clinical reference. We also discuss the robustness of multiparametric models in distinguishing different stages of disease development within specific disease contexts. These advancements not only reflect the potential value of high-resolution vascular imaging technology and the application of quantitative characterizations but also provide new insights into their promising prospects for advancing fundamental biomedical research and clinical diagnosis.