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Optimized GPU histograms for multi-modal registration

机译:优化的GPU直方图用于多模式配准

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摘要

GPU-based systems are used more and more for medical image processing because of their parallel processing power and memory bandwidth. Impressive results have been achieved when registering large volume, however, one of themost-used similarity measures for multi-modal registration - mutual information - is not well suited for the streaming architecture because of its memory access pattern. We present two optimization approaches that improve the performance by a factor of four compared to state-of-the-art GPU algorithms in the latest research papers.
机译:基于GPU的系统具有并行处理能力和内存带宽,因此越来越多地用于医学图像处理。大量注册时已经取得了令人印象深刻的结果,但是,多模式注册中最常用的相似性措施之一(互信息)由于其内存访问模式而不太适合流传输体系结构。与最新的研究论文中的最新GPU算法相比,我们提供了两种将性能提高四倍的优化方法。

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