2D/3D image fusion is used for a variety of interventional procedures. Overlays of 2D images with perspective-correctly rendered 3D images provide the physicians additional information during the interventions. In this work, a real-time capable 2D/3D registration framework is presented. An adapted parallelization using GPU is investigated for the depth-aware registration algorithm. The GPU hardware architecture is specially taken into account by optimizing memory access patterns and exploiting CUDA-texture memory. The real-time capability is achieved with a median runtime of one 2D/3D registration iteration of 86.1 ms with an median accuracy of up to 1.15 mm.
CITATION STYLE
Utzschneider, M., Wang, J., Schaffert, R., Borsdorf, A., & Maier, A. (2017). Real-time-capable GPU-framework for depth-aware rigid 2D/3D registration. In Informatik aktuell (pp. 185–190). Kluwer Academic Publishers. https://doi.org/10.1007/978-3-662-54345-0_43
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