Computed tomography angiography (CTA) has become a mainstay for the imaging of vascular diseases, because of high accuracy, availability, and rapid turnaround time. High-quality CTA images can now be routinely obtained with high isotropic spatial resolution and temporal resolution. Advances in CTA have focused on improving the image quality, increasing the acquisition speed, eliminating artifacts, and reducing the doses of radiation and iodinated contrast media. Dual-energy computed tomography provides material composition capabilities that can be used for characterizing lesions, optimizing contrast, decreasing artifact, and reducing radiation dose. Deep learning techniques can be used for classification, segmentation, quantification, and image enhancement.