Abstract
Compute Unified Device Architecture (CUDA) is a parallel computing platform and programming model invented by NVIDIA. It enables dramatic increase in computing performance via the power of the graphics processing unit (GPU). In medical image analysis, 3D image registration generally takes relatively long time, which is not feasible for clinical applications. To solve this problem, this paper proposed a high performance computational method based on CUDA, which took full advantage of GPU parallel computing under CUDA architecture combined with image multiple scale and maximum mutual information. Experiments showed that this algorithm can not only maintain the registration accuracy but also greatly increase the speed of registration process and meet the real-time requirement of clinical application.
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