Efficient registration method of medical images using GPU

Registration of medical images is an important task; however, automatic image-based registration is computationally expensive. Given this task, the authors propose an efficient rigid registration method, which is based on mutual information and uses a graphics processing unit (GPU). Mutual-information-based registration methods require joint-histogram computation. Although a GPU can provide high performance computing, a joint histogram has a large number of bins, and the computation of such a histogram is not suitable for a GPU (whose shared memory is limited). Taking advantage of the fact that one image (the reference image) is not transformed during the registration process, the proposed method computes a joint histogram by computing multiple one-dimensional histograms and combining them. The method can therefore be efficiently implemented on a GPU even with limited shared memory. Experimental results for 256 x 256 x 256 image registration show that the method is about 140 times faster than a standard implementation on a CPU and 2.6 times faster than previous methods using GPUs.