首页> 外文会议>IEEE International Symposium on Biomedical Imaging >EVALUATION OF BRAIN IMAGE NONRIGID REGISTRATION ALGORITHMS BASED ON LOG-EUCLIDEAN MR-DTI CONSISTENCY MEASURES
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EVALUATION OF BRAIN IMAGE NONRIGID REGISTRATION ALGORITHMS BASED ON LOG-EUCLIDEAN MR-DTI CONSISTENCY MEASURES

机译:基于Log-Euclidean MR-DTI一致性措施的脑图像非防引登记算法的评估

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Several nonrigid registration algorithms have been proposed for inter-subject alignment, used to construct statistical atlases and to identify group differences. Assessment of the accuracy of nonrigid registration algorithms is an essential and complex issue due to its intricate framework and its application-dependent behavior. We demonstrate that the diffusion MRI provides an independent means of assessing the quality of alignment achieved on the structural MRI. Diffusion tensor MRI (DT-MRI) enables the comparison of the local position and orientation of regions that appear homogeneous in conventional MRI. We carried out inter-subject alignment of conventional Tl-weighted MRI with three different registration algorithms. Consequently, we projected DT-MRI of each subject through the same inter-subject transformation. The quality of the inter-subject alignment is assessed by estimating the consistency of the aligned DT-MRI using the Log-Euclidean framework.
机译:已经提出了几种非重量注册算法用于对象间对齐,用于构建统计统计概括和识别组差异。由于其复杂的框架及其应用依赖行为,评估非身份登记算法的准确性是一个重要的和复杂的问题。我们表明扩散MRI提供了评估结构MRI上实现的对准质量的独立手段。扩散张量MRI(DT-MRI)使得能够比较常规MRI在均匀的区域的局部位置和取向。我们用三种不同的登记算法进行了传统的TL加权MRI的对象间对齐。因此,我们通过相同的对象间转换投影了每个受试者的DT-MRI。通过使用Log-euclidean框架估计对齐的DT-MRI的一致性来评估对象间对准的质量。

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