Voxel similarity measures for 3-D serial MR brain image registration
Voxel similarity measures for 3-D serial MR brain image registration
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DOI：
10.1109/42.836369
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发表时间：
2000-02-01
影响因子：
10.6
通讯作者：
Hawkes, DJ
中科院分区：
文献类型：
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作者：
Holden, M;Hill, DLG;Hawkes, DJ
我们评估了八种不同的相似性度量，用于连续磁共振(MR)脑扫描刚体配准。为了评估它们的准确性，我们使用了33个临床三维(3-D)序列MR图像，通过手动分割排除了可变形的硬膜外组织，并模拟了添加了强度失真的3D MR图像。对于每个度量，我们确定了分段和未分段数据集的配准变换的一致性。我们已经表明，在测试的八个度量中，基于联合熵的度量产生了最好的一致性。特别是，这些措施似乎对硬膜外组织的存在最不敏感。对于这些数据，无论有没有大脑分割，这些联合熵测量的准确性差异都在差异图像中视觉可检测到的变化的阈值内。
We have evaluated eight different similarity measures used for rigid body registration of serial magnetic resonance (MR) brain scans. To assess their accuracy we used 33 clinical three-dimensional (3-D) serial MR images, with deformable extradural tissue excluded by manual segmentation and simulated 3-D MR images with added intensity distortion. For each measure we determined the consistency of registration transformations for both sets of segmented and unsegmented data. We have shown that of the eight measures tested, the ones based on joint entropy produced the best consistency. In particular, these measures seemed to be least sensitive to the presence of extradural tissue. For these data the difference in accuracy of these joint entropy measures, with or without brain segmentation, was within the threshold of visually detectable change in the difference images.