Geodesic based tractography on diffusion magnetic resonance data is a method to devise long distance connectivities among the brain regions. In this study, cellular automata technique is applied to the geodesic tractography problem and the algorithm is implemented on a graphics processing unit. Cellular automaton based method is preferable to current techniques due to its parallel nature and ability to solve the connectivity based segmentation problem with the same computational complexity, which has important applications in neuroimaging. An application to prior-less tracking and connectivity based segmentation of corpus callosum fibers is presented as an example. A geodesic tractography based corpus callosum atlas is provided, which reveals high projections to the cortical language areas. The developed method not only allows fast computation especially for segmentation but also provides a powerful and intuitive framework, suitable to derive new algorithms to perform connectivity calculations and allowing novel applications.

中文翻译：

---

细胞自动机术：基于GPU的快速测地扩散MR术和基于连接的分割。

在扩散磁共振数据上基于大地测量的束线照相术是一种在大脑区域之间设计长距离连接性的方法。在这项研究中，将细胞自动机技术应用于测地线束学问题，并在图形处理单元上实现该算法。基于元胞自动机的方法由于其并行性和能够以相同的计算复杂度解决基于连通性的分割问题的能力而优于当前技术，这在神经成像中具有重要的应用。举例说明了基于to体跟踪和基于连接的call体纤维分割的应用。提供了基于测地线术的体图集，该图集显示了对皮层语言区域的高度投影。