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 onedimensional
histograms and combining them. The method can therefore be efficiently implemented on a GPU
even with limited shared memory. Experimental results for 256 × 256 × 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.
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