Faculdade de Engenharia da Universidade do Porto, Instituto de Engenharia Mecânica e Gestão Industrial, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal.
Med Biol Eng Comput. 2011 Mar;49(3):313-23. doi: 10.1007/s11517-010-0700-4. Epub 2010 Nov 3.
This article presents a framework to register (or align) plantar pressure images based on a hybrid registration approach, which first establishes an initial registration that is subsequently improved by the optimization of a selected image (dis)similarity measure. The initial registration has two different solutions: one based on image contour matching and the other on image cross-correlation. In the final registration, a multidimensional optimization algorithm is applied to one of the following (dis)similarity measures: the mean squared error (MSE), the mutual information, and the exclusive or (XOR). The framework has been applied to intra- and inter-subject registration. In the former, the framework has proven to be extremely accurate and fast (<70 ms on a normal PC notebook), and obtained superior XOR and identical MSE values compared to the best values reported in previous studies. Regarding the inter-subject registration, by using rigid, similarity, affine, projective, and polynomial (up to the fourth degree) transformations, the framework significantly optimized the image (dis)similarity measures. Thus, it is considered to be very accurate, fast, and robust in terms of noise, as well as being extremely versatile, all of which are regarded as essential features for near-real-time applications.
本文提出了一种基于混合配准方法的足底压力图像配准（或对齐）框架，该方法首先建立初始配准，然后通过优化选择的图像（不）相似性度量来改进初始配准。初始配准有两种不同的解决方案：一种基于图像轮廓匹配，另一种基于图像互相关。在最终配准中，多维优化算法应用于以下（不）相似性度量之一：均方误差 (MSE)、互信息和异或 (XOR)。该框架已应用于内-间体配准。在前者中，该框架被证明是极其准确和快速的（在普通笔记本电脑上<70ms），并且与之前研究报告的最佳值相比，获得了更高的 XOR 和相同的 MSE 值。关于间体配准，通过使用刚体、相似、仿射、投影和多项式（最高四阶）变换，该框架显著优化了图像（不）相似性度量。因此，它被认为在噪声方面非常准确、快速和稳健，并且非常通用，所有这些都被认为是近实时应用的基本特征。
