  The potential benefit of hybrid X-ray and MR imaging in the interventional
environment is large due to the combination of fast imaging with high contrast
variety. However, a vast amount of existing image enhancement methods requires
the image information of both modalities to be present in the same domain. To
unlock this potential, we present a solution to image-to-image translation from
MR projections to corresponding X-ray projection images. The approach is based
on a state-of-the-art image generator network that is modified to fit the
specific application. Furthermore, we propose the inclusion of a gradient map
in the loss function to allow the network to emphasize high-frequency details
in image generation. Our approach is capable of creating X-ray projection
images with natural appearance. Additionally, our extensions show clear
improvement compared to the baseline method.
