Registration of multi-modal brain images using the rigidity constraint

L. Ding, A. Goshtasby
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引用次数: 3

Abstract

A template-matching approach to registration of volumetric images is described. The process automatically selects about a dozen highly detailed and unique templates (cubic or spherical subvolumes) from the target volume and locates the templates in the reference volume. The centroids of four correspondences best satisfying the rigidity constraint are then used to determine the transformation matrix that resamples the target volume to overlay the reference volume. Different similarity measures used in template matching are discussed and experimental results are presented. The proposed registration method produces a median error of 2.8 mm when registering Venderbilt brain image data sets and an average registration time of 2.5 minutes on a 400 MHz PC.
基于刚性约束的多模态脑图像配准
描述了一种用于体积图像配准的模板匹配方法。该过程自动从目标卷中选择大约12个非常详细和独特的模板(立方或球形子卷),并将模板定位在参考卷中。然后使用最满足刚性约束的四个对应的质心来确定变换矩阵,该变换矩阵对目标体进行重采样以覆盖参考体。讨论了模板匹配中不同的相似度度量方法,并给出了实验结果。所提出的配准方法对Venderbilt脑图像数据集的配准误差中值为2.8 mm,在400mhz PC上的平均配准时间为2.5分钟。
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