Regularization of diffusion-based direction maps for the tracking of brain white matter fascicles
Regularization of diffusion-based direction maps for the tracking of brain white matter fascicles
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DOI：
10.1006/nimg.2000.0607
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发表时间：
2000-08-01
期刊：
影响因子：
5.7
通讯作者：
Mangin, JF
中科院分区：
文献类型：
--
作者：
Poupon, C;Clark, CA;Mangin, JF
磁共振弥散张量成像（DTI）提供了脑白质纤维局部方向的信息。本文从这些扩散数据出发，讨论了由许多纤维组成的束所引起的连通性的推断。通常的束束跟踪思路是跟随局部扩散最高的方向，由于纤维交叉引起的问题，容易产生错误的分叉。在本文中，这一困难部分地克服了使用的先验知识的低曲率的大多数束。这些知识被嵌入到白质的意大利面板表示的弯曲能量模型中，用于计算正则束束方向图。然后提出了一种新的跟踪算法来突出显示该方向图中假定的束状体轨迹。该算法考虑了神经束之间潜在的扇形连接。提出了一种基于先验知识影响的跟踪行为研究方法，并举例说明了利用活体人脑数据获得的具体跟踪结果。这些结果包括一些锥体、联合纤维和各种联合纤维的假定轨迹。(C) 2000年学术出版社。
Magnetic resonance diffusion tensor imaging (DTI) provides information about fiber local directions in brain white matter. This paper addresses inference of the connectivity induced by fascicles made up of numerous fibers from such diffusion data. The usual fascicle tracking idea, which consists of following locally the direction of highest diffusion, is prone to erroneous forks because of problems induced by fiber crossing. In this paper, this difficulty is partly overcomed by the use of a priori knowledge of the low curvature of most of the fascicles. This knowledge is embedded in a model of the bending energy of a spaghetti plate representation of the white matter used to compute a regularized fascicle direction map. A new tracking algorithm is then proposed to highlight putative fascicle trajectories from this direction map. This algorithm takes into account potential fan shaped junctions between fascicles. A study of the tracking behavior according to the influence given to the a priori knowledge is proposed and concrete tracking results obtained with in vivo human brain data are illustrated. These results include putative trajectories of some pyramidal, commissural, and various association fibers. (C) 2000 Academic Press.