A Frequency Domain Constraint for Synthetic X-ray Image Super Resolution.

2021 
Synthetic X-ray images can be helpful for image guiding systems and VR simulations. However, it is difficult to produce high-quality arbitrary view synthetic X-ray images in real-time due to limited CT scanning resolution, high computation resource demand or algorithm complexity. Our goal is to generate high-resolution synthetic X-ray images in real-time by upsampling low-resolution im-ages. Reference-based Super Resolution (RefSR) has been well studied in recent years and has been proven to be more powerful than traditional Single Image Su-per-Resolution (SISR). RefSR can produce fine details by utilizing the reference image but it still inevitably generates some artifacts and noise. In this paper, we propose texture transformer super-resolution with frequency domain (TTSR-FD). We introduce frequency domain loss as a constraint to further improve the quality of the RefSR results with fine details and without obvious artifacts. This makes a real-time synthetic X-ray image-guided procedure VR simulation system possible. To the best of our knowledge, this is the first paper utilizing the frequency domain as part of the loss functions in the field of super-resolution. We evaluated TTSR-FD on our synthetic X-ray image dataset and achieved state-of-the-art results.
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