Tractography traces the peak directions extracted from fiber orientation distribution (FOD) suffering from ambiguous spatial correspondences between diffusion directions and fiber geometry, which is prone to producing erroneous tracks while missing true positive connections. The peaks-based tractography methods 'locally' reconstructed streamlines in 'single to single' manner, thus lacking of global information about the trend of the whole fiber bundle. In this work, we propose a novel tractography method based on a bundle-specific tractogram distribution function by using a higher-order streamline differential equation, which reconstructs the streamline bundles in 'cluster to cluster' manner. A unified framework for any higher-order streamline differential equation is presented to describe the fiber bundles with disjoint streamlines defined based on the diffusion tensor vector field. At the global level, the tractography process is simplified as the estimation of bundle-specific tractogram distribution (BTD) coefficients by minimizing the energy optimization model, and is used to characterize the relations between BTD and diffusion tensor vector under the prior guidance by introducing the tractogram bundle information to provide anatomic priors. Experiments are performed on simulated Hough, Sine, Circle data, ISMRM 2015 Tractography Challenge data, FiberCup data, and in vivo data from the Human Connectome Project (HCP) data for qualitative and quantitative evaluation. The results demonstrate that our approach can reconstruct the complex global fiber bundles directly. BTD reduces the error deviation and accumulation at the local level and shows better results in reconstructing long-range, twisting, and large fanning tracts.

翻译：纤维束示踪技术通过追踪纤维取向分布提取的峰值方向进行重建，但扩散方向与纤维几何结构之间存在空间对应模糊的问题，容易产生错误轨迹并遗漏真实阳性连接。基于峰值追踪的方法以"单对单"方式局部重建流线，缺乏对完整纤维束走向的全局信息。本文提出一种基于纤维束特异示踪图分布函数的新型追踪方法，通过高阶流线微分方程以"簇对簇"方式重建流线束。我们建立了统一的高阶流线微分方程框架，基于扩散张量向量场描述具有非连续流线的纤维束。在全局层面，追踪过程简化为通过最小化能量优化模型估计纤维束特异示踪图分布系数，并引入示踪图束信息提供解剖先验，以刻画BTD与扩散张量向量在先验引导下的关系。实验采用模拟霍夫、正弦、圆形数据、ISMRM 2015纤维束追踪挑战赛数据、FiberCup数据以及人类连接组计划活体数据进行定性和定量评估。结果表明，该方法可直接重建复杂的全局纤维束。BTD在局部层面降低了误差偏差与累积效应，在重建长程、扭转及大角度扇形纤维束方面展现了更优性能。