Pulmonary embolism (PE) is a potentially-fatal disease in which blood clots (i.e., emboli) break free from the deep veins in the body and migrate to the lungs. In order to prevent PE, anticoagulation therapy is often used; however, for some patients, it is contraindicated. For such patients, a mechanical filter, namely an inferior vena cava (IVC) filter, is inserted into the IVC to capture and prevent emboli from reaching the lungs. There are numerous IVC filter designs, and it is not well understood which particular IVC filter geometry will result in the best clinical outcome for a given patient. Patient-specific computational fluid dynamic (CFD) simulations may be used to aid physicians in IVC filter selection and placement. In particular, such computational simulations may be used to determine the capability of various IVC filters in various positions to capture emboli, while not creating additional emboli or significantly altering the flow of blood in the IVC. In this paper, we propose a computational pipeline that can be used to generate patient-specific geometric models and computational meshes of the IVC and IVC filter for various IVC anatomies based on the patient’s computer tomography (CT) images. Our pipeline involves several steps including image processing, geometric model construction, surface and volume mesh generation, and CFD simulation. We then use our patient-specific meshes of the IVC and IVC filter in CFD simulations of blood flow, whereby we demonstrate the potential utility of this approach for optimized, patient-specific IVC filter selection and placement for improved prevention of PE. The novelty of our approach lies in the use of a superelastic mesh warping technique to virtually place the surface mesh of the IVC filter (which was created via computer-aided design modeling) inside the surface mesh of the patient-specific IVC, reconstructed from clinical CT data. We also employ a linear elastic mesh warping technique to simulate the deformation of the IVC when the IVC filter is placed inside of it.