Large vessel disease is characterized by localized or diffuse accumulation of atherosclerotic plaques, resulting in restricted blood flow, whereas small vessel disease arises from endothelial dysfunction and inflammation that impair tissue perfusion independent of plaque buildup. The interplay between large and small vessel pathologies crucially limits the capacity of the circulatory system to supply adequate blood to tissues, with particularly prominent manifestations in the coronary and peripheral vascular beds. Diagnostic evaluation typically relies on X-ray angiography, wherein a contrast agent is administered to visualize the dynamic passage and clearance of blood through targeted vessels. Historically, these angiograms have been constrained to anatomical quantification of stenosis within large vessels. Functional assessments—including fractional flow reserve (FFR), index of microvascular resistance (IMR), and flow reserve—are conducted to characterize vascular function; however, these techniques are invasive and present interpretative challenges. Given the substantial volume of cardiac and peripheral catheterization procedures performed and the limitations inherent in current diagnostic strategies, there is an urgent need for methodologies capable of extracting diagnostically relevant information regarding both large and small vessel disease directly from X-ray angiography. Our research group has developed advanced computational and machine learning approaches for both anatomical and functional characterization of vascular pathology using angiography. Specifically, our suite of tools comprises: (1) convolutional neural networks for angiogram segmentation [1]; (2) multi-fidelity reduced-order models for efficient and accurate assessment of large vessel disease [2]; and (3) data-driven frameworks for evaluating microvascular disease [3][4]. In this work, we will provide an overview of these technologies and highlight their application across a range of studies, including recent innovations aimed at assessing microcirculatory health in patients with peripheral artery disease.