Zhang Hui, Yushkevich Paul A, Rueckert Daniel, Gee James C
Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, Philadelphia, USA.
Med Image Comput Comput Assist Interv. 2007;10(Pt 2):211-8. doi: 10.1007/978-3-540-75759-7_26.
This paper describes an algorithm for unbiased construction of white matter (WM) atlases using full information available to diffusion tensor (DT) images. The key component of the proposed algorithm is a novel DT image registration method that leverages metrics comparing tensors as a whole and optimizes tensor orientation explicitly. The problem of unbiased atlas construction is formulated using the approach proposed by Joshi et al., i.e., the unbiased WM atlas is determined by finding the mappings that best match the atlas to the images in the population and have the least amount of deformation. We show how the proposed registration algorithm can be adapted to approximately find the optimal atlas. The utility of the proposed approach is demonstrated by constructing a WM atlas of 13 subjects. The presented DT registration method is also compared to the approach of matching DT images by aligning their fractional anisotropy images using large-deformation image registration methods. Our results suggest that using full tensor information can better align the orientations of WM fiber bundles.
本文描述了一种利用扩散张量（DT）图像的全部可用信息无偏构建白质（WM）图谱的算法。该算法的关键组成部分是一种新颖的DT图像配准方法，该方法利用整体比较张量的度量并明确优化张量方向。无偏图谱构建问题采用Joshi等人提出的方法来表述，即通过找到使图谱与总体图像最佳匹配且变形量最小的映射来确定无偏WM图谱。我们展示了如何调整所提出的配准算法以近似找到最优图谱。通过构建13名受试者的WM图谱证明了所提方法的实用性。还将所提出的DT配准方法与使用大变形图像配准方法对齐分数各向异性图像来匹配DT图像的方法进行了比较。我们的结果表明，使用全张量信息可以更好地对齐WM纤维束的方向。
