Multimodal registration via mutual information incorporating geometric and spatial context.
Multimodal registration via mutual information incorporating geometric and spatial context.
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DOI：
10.1109/tip.2014.2387019
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发表时间：
2015-02
期刊：
影响因子：
--
通讯作者：
Prince JL
中科院分区：
文献类型：
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作者：
Woo J;Stone M;Prince JL
多模态图像配准是一类从不同模态中找到对应关系的算法。由于不同的模式不表现出相同的特征，找到准确的对应关系仍然是一个挑战。为了处理这个问题，基于互信息（MI）的配准已经成为优选选择，因为MI是基于待配准的两个体积之间的统计关系。然而，MI有一些局限性。首先，当体积中存在局部强度变化时，基于MI的配准常常失败。第二，MI只考虑两个体积之间的统计强度关系，而忽略了关于体素的空间和几何信息。在这项工作中，我们建议通过将空间和几何信息通过3D哈里斯算子来解决这些限制。具体来说，我们专注于高分辨率图像和低分辨率图像之间的配准。MI成本函数在存在大的空间变化的区域（诸如角或边缘）中计算。此外，MI成本函数被增强与几何信息来自应用于高分辨率图像的3D哈里斯算子。所提出的方法的鲁棒性和准确性进行了证明，使用实验的合成和临床数据，包括大脑和舌头。所提出的方法提供了准确的配准，并产生了更好的性能比标准的配准方法。
Multimodal image registration is a class of algorithms to find correspondence from different modalities. Since different modalities do not exhibit the same characteristics, finding accurate correspondence still remains a challenge. In order to deal with this, mutual information (MI) based registration has been a preferred choice as MI is based on the statistical relationship between both volumes to be registered. However, MI has some limitations. First, MI based registration often fails when there are local intensity variations in the volumes. Second, MI only considers the statistical intensity relationships between both volumes and ignores the spatial and geometric information about the voxel. In this work, we propose to address these limitations by incorporating spatial and geometric information via a 3D Harris operator. Specifically, we focus on the registration between a high-resolution image and a low-resolution image. The MI cost function is computed in the regions where there are large spatial variations such as corner or edge. In addition, the MI cost function is augmented with geometric information derived from the 3D Harris operator applied to the high-resolution image. The robustness and accuracy of the proposed method were demonstrated using experiments on synthetic and clinical data including the brain and the tongue. The proposed method provided accurate registration and yielded better performance over standard registration methods.