Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1117/12.2512195 | Proceedings of SPIE |
DocType | Volume | ISSN |
Conference | 10949 | 0277-786X |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bernhard Stimpel | 1 | 1 | 1.36 |
| Christopher Syben | 2 | 21 | 6.40 |
| Tobias Würfl | 3 | 52 | 10.53 |
| Katharina Breininger | 4 | 3 | 5.85 |
| Katrin Mentl | 5 | 3 | 0.78 |
| Jonathan Lommen | 6 | 0 | 0.68 |
| Arnd Dörfler | 7 | 20 | 6.06 |
| Andreas K. Maier | 8 | 560 | 178.76 |