Velocity measurements from medical imaging technologies such as magnetic resonance imaging and Doppler ultrasound are widely used in the clinic to help diagnose and treat vascular disease. At present, however, it is difficult to extract from in vivo velocity measurements the detailed hemodynamic information (e.g. wall shear stress and residence time) routinely available from computational fluid dynamic (CFD) studies. Our research efforts are therefore currently directed at extending CFD-based techniques to novel in vivo imaging applications where such detailed hemodynamic information is required. In this context we define “computational imaging” as the use of computer modeling and visualization techniques to mimic, enhance, or extend the capabilities of conventional medical imaging. In this presentation we describe areas of active research in which we are developing and applying such computational imaging techniques to further the basic understanding, diagnosis and treatment of vascular disease.