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Volume image registration remains one of the best candidates for Graphics Processing Unit (GPU) acceleration because of its enormous computation time and plentiful data-level parallelism. However, an efficient GPU implementation for image registration is still challenging due to the heavy utilization of expensive atomic operations for similarity calculations. In this paper, we first propose five GPU-friendly...
Volume image registration is a basic component of medical image processing which traditionally requires long computation time. In this paper, we propose five Correlation Ratio based schemes that explore the design space for Graphics Processing Unit (GPU) acceleration. Through comparisons among these five schemes, we present the trade-off between benefits and overheads of introducing shadow histograms...
In recent years, mutual information has developed as a popular image registration measure especially in multimodality image registration. However, based on Shannon entropy, it focuses on the relationships between corresponding individual pixels and not those neighboring pixels. It ignores the spatial information contained in the images such as edges and corners that might be useful in the image registration...
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