Image similarity and tissue overlaps as surrogates for image registration accuracy: widely used but unreliable.
Image similarity and tissue overlaps as surrogates for image registration accuracy: widely used but unreliable.
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DOI：
10.1109/tmi.2011.2163944
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发表时间：
2012-02
影响因子：
10.6
通讯作者：
Rohlfing T
中科院分区：
文献类型：
--
作者：
Rohlfing T
非刚性图像配准的准确性通常使用替代测量来近似，例如组织标签重叠分数、图像相似性、图像差异或变换逆一致性误差。本文提供的实验证据表明，这些措施，即使在组合使用时，不能区分准确的不准确的注册。为此，我们引入了一个“注册”算法，产生高度不准确的图像变换，但表现非常好的替代措施。在测试的标准中，只有局部解剖区域的重叠评分可靠地区分合理配准和不准确配准，而图像相似性和组织重叠则不能区分。我们的结论是，组织重叠和图像相似性，无论单独使用还是一起使用，都不能为准确配准提供有效证据，因此不应被报告或接受。
The accuracy of nonrigid image registrations is commonly approximated using surrogate measures such as tissue label overlap scores, image similarity, image difference, or transformation inverse consistency error. This paper provides experimental evidence that these measures, even when used in combination, cannot distinguish accurate from inaccurate registrations. To this end, we introduce a “registration” algorithm that generates highly inaccurate image transformations, yet performs extremely well in terms of the surrogate measures. Of the tested criteria, only overlap scores of localized anatomical regions reliably distinguish reasonable from inaccurate registrations, whereas image similarity and tissue overlap do not. We conclude that tissue overlap and image similarity, whether used alone or together, do not provide valid evidence for accurate registrations and should thus not be reported or accepted as such.