gVirtualXray (gVXR) is an open-source framework that relies on the Beer-Lambert law to simulate X-ray images in realtime on a graphics processor unit (GPU) using triangular meshes. We produced four Jupyter Notebooks to compare images simulated with gVXR and ground truth image of an anthropomorphic phantom: (i) an X-ray projection generated using a Monte Carlo simulation code, (ii) real digitally reconstructed radiographs (DRRs), (iii) computed tomography (CT) slices, and (iv) a real radiograph acquired with a clinical X-ray imaging system. Image registration was deployed in two Notebooks to align the simulated image on the corresponding ground truth image. We demonstrated that accurate images can be generated in milliseconds with gVirtualXray when scattering can be ignored.