快速鲁棒的三维膝关节运动学多模态图像配准

Shabnam Saadat, M. Pickering, D. Perriman, J. Scarvell, Paul N. Smith
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引用次数: 10

摘要

对从不同设备或成像协议获得的两幅或多幅图像进行空间对齐的过程称为多模态图像配准。由于所使用的相似性度量是该过程中最重要的方面之一,因此提出了一些增强多模态图像配准的措施。然而,目前可用的测量方法要么不够准确,要么计算成本非常高。本文提出了一种新的混合多模态配准方法。该方法结合了基于图像边缘匹配的快速度量和基于两幅待配准图像的联合概率分布的稳健但缓慢度量。我们的实验结果表明,使用这种混合方法提供了与以前的最佳度量相当的性能,但大大减少了计算时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast and Robust Multi-Modal Image Registration for 3D Knee Kinematics
The process of spatially aligning two or more images acquired from different devices or imaging protocols is known as multi-modal image registration. As the similarity measure used is one of the most significant aspects of this process, certain measures have been proposed to enhance multi-modal image registration. However, the currently available measures are either not sufficiently accurate or are very computationally expensive. In this paper, a new hybrid multimodal registration approach is proposed. The new approach combines a fast measure, based on matching image edges, with a robust, but slow measure, which uses the joint probability distribution of the two images to be registered. Our experimental results reveal that using this hybrid approach provides a performance equivalent to the previously best measures but with a significantly reduced computational time.
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