GPU accelerated simulations of magnetic resonance imaging of vascular structures
Abstract
Computer simulations of magnetic resonance imaging (MRI) are important tools in improving this imaging modality and developing new imaging techniques. However, MRI models often have to be simplified to enable simulations to be carried out in a reasonable time. The computational complexity associated with the tracking of magnetic fields’ perturbations with high spatial and temporal resolutions is very high and, thus, it calls for using parallel computing environments. In this paper, we present a GPU-based parallel approach to simulate MRI of vascular structures. The magnetization calculation in different spatial coordinates is spread over GPU cores. We apply CUDA framework and take advantage of GPU memory hierarchy to efficiently exploit GPU computational power. Experimental results with different GPUs and various images show that the proposed algorithm substantially speedups the simulation. The proposed GPU-based approach may be easily adopted in modeling of other flow related phenomena like perfusion or diffusion. © Springer International Publishing Switzerland 2016.
Keywords
Computer graphics equipment
Computer simulation
Imaging techniques
Magnetism
Parallel processing systems
Program processors
Resonance
Computational power
Graphics Processing Unit
Imaging modality
Memory hierarchy
Parallel-computing environment
Spatial and temporal resolutions
Spatial coordinates
Vascular structures
Magnetic resonance imaging
Computer graphics