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Accelerate multi-dimensional CT scanner simulation with GPU

CT scanner simulation virtually simulates the projection process of CT without actually scanning. It is very useful to design, evaluate and develop CT systems which are evolving into some directions. However, in order to simulate multiple detector rows, multiple x-ray energy and other dimensions simultaneously, it becomes time consuming because of large amount of computation. In this paper, we present a solution to this problem with CUDA architecture on GPU. Our solution contains three steps. First, CPU prepares the data that will be used by GPU. Then, GPU kernel is launched to calculate the projection of all rays through the phantom data in parallel. In order to get maximum memory bandwidth, we optimized the data storage by padding 2D arrays to ensure the global memory access coalesced. Finally, post processing is done on CPU. Our experiment environment includes a dual core CPU and a NVIDIA Quadro FX 1800 GPU with CUDA compute capability 1.1. We used three kinds of phantom data to test the performance. It is found that our solution gets the same image quality in double precision but gains a speed increase of more than 10 times faster than using CPU only.