基于互信息计算和模式搜索优化的FPGA可变形图像配准加速方法

Asish Dutta, S. Mukhopadhyaya, P. S. Sastry
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引用次数: 0

摘要

变形场的实时计算对于时间要求严格的自动变形图像配准算法至关重要。然而,目前的微处理器的计算能力不足以对其进行实时计算;因此,需要使用大规模并行计算机或特定于应用程序的硬件加速器来实现。提出了一种计算互信息的顺序管道,可以更快地实现可变形图像配准过程。采用以互信息(MI)为代价函数的分层图像细分配准算法。本文提出了一种低内存的MI计算并行实现。图像配准的最终目标是通过软件和硬件实现,其中主机执行模式搜索优化(PSO), FPGA计算优化所需的MI。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An approach to accelerate deformable image registration by FPGA based mutual information calculation and pattern search optimization
Real time computation of deformation fields is essential for automated deformable image registration algorithms for time critical applications. However, the computational power of current microprocessors is not sufficient for real time computation of it; therefore requiring implementations using either massively parallel computers or application-specific hardware accelerators. A sequential pipeline for the calculation of mutual information is presented which allows a faster implementation of deformable image registration process. Hierarchical image subdivision based registration algorithm with mutual information (MI) as the cost function is used. A low memory parallel implementation of MI calculation is proposed here. The final objective of image registration is achieved by a software and hardware implementation, where host computer performs pattern search optimization (PSO) and FPGA calculates MI required for optimization.
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