使用扩散张量成像数据重建脑白质纤维的新算法

由磁共振扩散张量成像（DT-MRI）可以获得扩散的方向性信息，利用这些信息可以无创地重建人脑的白质纤维，而且这也是目前在活体上重建脑白质纤维的唯一方法．然而由于磁共振成像设备与成像技术的限制，纤维重建过程中会遇到许多困难，例如：DT-MRI的数据是离散的，而所要重建的纤维是连续的；而且由相对较低的MRI空间分辨率所引起的部分容积效应会影响DT—MRI的数据质量．针对这些问题，提出了一种加权跟踪算法．该算法结合经典物理理论，利用纤维跟踪过程中待定方向点周围相关体元的主向量与分量各向异性（FA）值来计算纤维跟踪线的前进方向．实验表明，该算法能够相对较好地解决重建过程中所存在的困难．从重建的效果看，该方法能够很好地反映脑白质纤维的分布情况．

Fiber Tracking of White Matter with Diffusion Tensor Imaging Data

The directional diffusion information obtained by diffusion tensor magnetic resonance imaging (DT- MRI) can be used to noninvasively visualize white matter fibers in human brain.It is the unique approach to vi- vo reconstruction of those fibers.However,the restrictions of hardware and imaging technology create some challenges for the reconstruction process,e.g.continuous fibers are indicated by the discrete signal on the DT- MRI,and partial volume effect caused by low spatial resolution negatively affects the DT-MRI results.To re- solve these problems,a weighting tracking algorithm is proposed.Principal eigenvectors and fractional anisotro- py (FA) values of the correlative voxels are used.Meanwhile,the principle of classical physics is applied to estimating the tracking direction of a fiber.Experiments show that the method solved the problems quite well and it has strong potential to depict the distribution of white matter fibers in the brain.