Holden M, Hill D L, Denton E R, Jarosz J M, Cox T C, Rohlfing T, Goodey J, Hawkes D J
Radiological Sciences and Medical Engineering, Guy's, King's and St Thomas' School of Medicine, King's College London, UK.
IEEE Trans Med Imaging. 2000 Feb;19(2):94-102. doi: 10.1109/42.836369.
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.
我们评估了用于串行磁共振（MR）脑部扫描刚体配准的八种不同相似性度量。为评估其准确性，我们使用了33例临床三维（3-D）串行MR图像，通过手动分割排除了可变形的硬膜外组织，并使用了添加了强度失真的模拟3-D MR图像。对于每种度量，我们确定了分割和未分割数据集的配准变换的一致性。我们已经表明，在测试的八种度量中，基于联合熵的度量产生了最佳的一致性。特别是，这些度量似乎对硬膜外组织的存在最不敏感。对于这些数据，这些联合熵度量在有或没有脑部分割情况下的准确性差异，在差异图像中视觉可检测变化的阈值范围内。
