Feature-based technique for automated image registration of the brain

L. Hsu, M. Loew
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Abstract

In this paper, we present an automated multi-modality registration algorithm based on hierarchical feature extraction. The approach, which has not ben used previously, can be divided into two distinct stages: feature extraction and geometric matching. Two kinds of corresponding features - edge and surface - are extracted hierarchically from various image modalities. The registration then is performed using least-squares matching of the automatically extracted features. Both the robustness and accuracy of feature extraction and geometric marching steps are evaluated using simulated and patient images. The preliminary results show the error is on the average of one voxel. We have shown the proposed 3D registration algorithm provides a simple and fast method for automatic registering of MR-to-CT and MR-to- PET image modalities. Our results are comparable to other techniques and require no user interaction.
基于特征的脑图像自动配准技术
本文提出了一种基于分层特征提取的多模态自动配准算法。该方法可分为两个不同的阶段:特征提取和几何匹配。从不同的图像模态中分层提取两种相应的特征——边缘和表面。然后使用自动提取的特征的最小二乘匹配进行配准。使用模拟图像和患者图像对特征提取和几何推进步骤的鲁棒性和准确性进行了评估。初步结果表明,误差平均为1体素。我们已经证明了所提出的三维配准算法为MR-to- ct和MR-to- PET图像模式的自动配准提供了一种简单快速的方法。我们的结果与其他技术相当,不需要用户交互。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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