Barmpoutis Angelos, Hwang Min Sig, Howland Dena, Forder John R, Vemuri Baba C
University of Florida, Gainesville, FL 32611, USA.
Neuroimage. 2009 Mar;45(1 Suppl):S153-62. doi: 10.1016/j.neuroimage.2008.10.056. Epub 2008 Nov 13.
In Diffusion Weighted Magnetic Resonance Image (DW-MRI) processing, a 2nd order tensor has been commonly used to approximate the diffusivity function at each lattice point of the DW-MRI data. From this tensor approximation, one can compute useful scalar quantities (e.g. anisotropy, mean diffusivity) which have been clinically used for monitoring encephalopathy, sclerosis, ischemia and other brain disorders. It is now well known that this 2nd-order tensor approximation fails to capture complex local tissue structures, e.g. crossing fibers, and as a result, the scalar quantities derived from these tensors are grossly inaccurate at such locations. In this paper we employ a 4th order symmetric positive-definite (SPD) tensor approximation to represent the diffusivity function and present a novel technique to estimate these tensors from the DW-MRI data guaranteeing the SPD property. Several articles have been reported in literature on higher order tensor approximations of the diffusivity function but none of them guarantee the positivity of the estimates, which is a fundamental constraint since negative values of the diffusivity are not meaningful. In this paper we represent the 4th-order tensors as ternary quartics and then apply Hilbert's theorem on ternary quartics along with the Iwasawa parametrization to guarantee an SPD 4th-order tensor approximation from the DW-MRI data. The performance of this model is depicted on synthetic data as well as real DW-MRIs from a set of excised control and injured rat spinal cords, showing accurate estimation of scalar quantities such as generalized anisotropy and trace as well as fiber orientations.
在扩散加权磁共振成像(DW-MRI)处理中,二阶张量通常用于近似DW-MRI数据每个格点处的扩散率函数。基于这种张量近似,可以计算出一些有用的标量(如各向异性、平均扩散率),这些标量已在临床上用于监测脑病、硬化症、局部缺血及其他脑部疾病。现在众所周知,这种二阶张量近似无法捕捉复杂的局部组织结构,如交叉纤维,因此,从这些张量导出的标量在这些位置会严重不准确。在本文中,我们采用四阶对称正定(SPD)张量近似来表示扩散率函数,并提出一种从DW-MRI数据估计这些张量的新技术,以保证其SPD特性。文献中已有几篇关于扩散率函数高阶张量近似的文章,但它们都没有保证估计值的正定性,而正定性是一个基本约束,因为扩散率的负值没有意义。在本文中,我们将四阶张量表示为三元四次式,然后应用关于三元四次式的希尔伯特定理以及岩泽参数化,以确保从DW-MRI数据得到SPD四阶张量近似。该模型的性能在合成数据以及一组切除的对照和损伤大鼠脊髓的真实DW-MRI上进行了描述,显示出对广义各向异性和迹等标量以及纤维方向的准确估计。