Xu Dongrong, Mori Susumu, Shen Dinggang, van Zijl Peter C M, Davatzikos Christos
Section of Biomedical Image Analysis, Department of Radiology, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania 19104, USA.
Magn Reson Med. 2003 Jul;50(1):175-82. doi: 10.1002/mrm.10489.
A method for the spatial normalization and reorientation of diffusion tensor (DT) fields is presented. Spatial normalization of tensor fields requires an appropriate reorientation of the tensor on each voxel, in addition to its relocation into the standardized space. This appropriate tensor reorientation is determined from the spatial normalization transformation and from an estimate of the underlying fiber direction. The latter is obtained by treating the principal eigenvectors of the tensor field around each voxel as random samples drawn from the probability distribution that represents the direction of the underlying fiber. This approach was applied to DT images from nine normal volunteers, and the results show a significant improvement in signal-to-noise ratio (SNR) after spatial normalization and averaging of tensor fields across individuals. The statistics of the spatially normalized tensor field, which represents the tensor characteristics of normal individuals, may be useful for quantitatively characterizing individual variations of white matter structures revealed by DT imaging (DTI) and deviations caused by pathology. Simulated experiments using this methodology are also described.
本文提出了一种用于扩散张量（DT）场的空间归一化和重新定向的方法。张量场的空间归一化除了要将张量重新定位到标准化空间外，还需要在每个体素上对张量进行适当的重新定向。这种适当的张量重新定向是根据空间归一化变换和对潜在纤维方向的估计来确定的。后者是通过将每个体素周围张量场的主特征向量视为从代表潜在纤维方向的概率分布中抽取的随机样本而获得的。该方法应用于9名正常志愿者的DT图像，结果表明，在对张量场进行空间归一化和个体间平均后，信噪比（SNR）有显著提高。空间归一化张量场的统计数据代表了正常个体的张量特征，可用于定量表征DT成像（DTI）揭示的白质结构的个体差异以及病理引起的偏差。还描述了使用该方法的模拟实验。
