Optimized GPU-Accelerated Framework for X-ray Rendering Using k-space Volume Reconstruction

X-ray rendering is recognized to be an important visualization technique in several scientific and engineering domains. It is capable of generating digital radiographs of volumetric data in the spatial domain using the X-ray transform with O(N-3) complexity. Alternatively, these radiographs can be reconstructed in the k-space in O(N(2)logN). This paper presents the architecture of an optimized X-ray volume rendering framework based on the Fourier slice theorem. The framework exploits the modern designs of Graphics Processing Units (GPUs). The rendering pipeline is designed to run entirely on the GPUs relying on the Compute Unified Device Architecture (CUDA) technology for computing all the data-parallel kernels and OpenGL for executing complementary geometrical operations. The interoperability between CUDA and OpenGL operations is addressed to optimize the workflow. The benchmarking results show that our framework is capable of rendering an X-ray projection of size 512(2) in 0.5 milli-seconds using a GeForce GTX 970 GPU.