Barmpoutis Angelos, Vemuri Baba C
CISE Department, University of Florida, Gainesville, FL 32611, USA.
Med Image Comput Comput Assist Interv. 2009;12(Pt 1):640-7.
Registration of Diffusion-Weighted MR Images (DW-MRI) can be achieved by registering the corresponding 2nd-order Diffusion Tensor Images (DTI). However, it has been shown that higher-order diffusion tensors (e.g. order-4) outperform the traditional DTI in approximating complex fiber structures such as fiber crossings. In this paper we present a novel method for unbiased group-wise non-rigid registration and atlas construction of 4th-order diffusion tensor fields. To the best of our knowledge there is no other existing method to achieve this task. First we define a metric on the space of positive-valued functions based on the Riemannian metric of real positive numbers (denoted by R+). Then, we use this metric in a novel functional minimization method for non-rigid 4th-order tensor field registration. We define a cost function that accounts for the 4th-order tensor re-orientation during the registration process and has analytic derivatives with respect to the transformation parameters. Finally, the tensor field atlas is computed as the minimizer of the variance defined using the Riemannian metric. We quantitatively compare the proposed method with other techniques that register scalar-valued or diffusion tensor (rank-2) representations of the DWMRI.
扩散加权磁共振图像(DW-MRI)的配准可以通过对相应的二阶扩散张量图像(DTI)进行配准来实现。然而,已经表明,高阶扩散张量(例如四阶)在逼近复杂纤维结构(如纤维交叉)方面优于传统的DTI。在本文中,我们提出了一种用于四阶扩散张量场的无偏组内非刚性配准和图谱构建的新方法。据我们所知,没有其他现有方法可以完成此任务。首先,我们基于正实数的黎曼度量(用R+表示)在正值函数空间上定义一个度量。然后,我们在一种用于非刚性四阶张量场配准的新型泛函最小化方法中使用此度量。我们定义一个代价函数,该函数考虑了配准过程中的四阶张量重新定向,并且相对于变换参数具有解析导数。最后,张量场图谱被计算为使用黎曼度量定义的方差的最小值。我们将所提出的方法与其他对DW-MRI的标量值或扩散张量(二阶)表示进行配准的技术进行了定量比较。