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首页> 外文期刊>Journal of Imaging Science and Technology >Hardware acceleration of mutual information-based 3D image registration
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Hardware acceleration of mutual information-based 3D image registration

机译：基于互信息的3D图像配准的硬件加速

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摘要

Real-time image registration is potentially an enabling technology for the effective and efficient use of many image-guided diagnostic and treatment procedures relying on multimodality image fusion or serial image comparison. Mutual information is currently the best-known image similarity measure for intensity-based multimodality image registration. The calculation of mutual information is memory intensive and does not benefit from cache-based memory architectures in standard software implementations, i.e., the calculation incurs a large number of cache misses. Previous attempts to perform image registration in real time focused on parallel supercomputer implementations, which achieved significant speedups using large, expensive supercomputers that are impractical for clinical deployment. We present a hardware architecture that can be used to accelerate a number of linear and elastic image registration algorithms that use mutual information as an image similarity measure. A proof-of-concept implementation of the architecture achieved speedups of 30 for linear registration and 100 for elastic registration against a 3.2 GHz Pentium III Xeon workstation. Further speedup can be achieved by using several modules in parallel.
机译：实时图像配准可能是一种依靠多模态图像融合或串行图像比较有效而有效地使用许多图像指导的诊断和治疗程序的使能技术。互信息当前是用于基于强度的多模态图像配准的最著名的图像相似性度量。互信息的计算会占用大量内存，并且无法从标准软件实现中的基于缓存的内存体系结构中受益，即，该计算会导致大量的缓存未命中。先前实时执行图像配准的尝试集中在并行超级计算机实现上，该实现使用大型，昂贵的超级计算机实现了显着的加速，而对于临床部署而言这是不切实际的。我们提出了一种硬件体系结构，可用于加速使用互信息作为图像相似性度量的许多线性和弹性图像配准算法。该架构的概念验证实现相对于3.2 GHz Pentium III Xeon工作站，线性配准的速度提高了30倍，弹性配准的速度提高了100倍。通过并行使用多个模块可以进一步提高速度。

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