Duan Ye, Heckenberg Greg, Xi Yongjian, Hao Dayang
Dept. of Comput. Sci., Missouri Univ., Columbia, MO 65211, USA.
Conf Proc IEEE Eng Med Biol Soc. 2006;2006:3628-31. doi: 10.1109/IEMBS.2006.260839.
In this paper, we propose a semi-automatic thalamus and thalamus nuclei segmentation algorithm from diffusion tensor magnetic resonance imaging (DT-MRI) based on the mean-shift algorithm. Comparing with existing thalamus segmentation algorithms which are mainly based on K-means algorithm, our mean-shift based algorithm is more flexible and adaptive. It does not assume a Gaussian distribution or a fixed number of clusters. Furthermore, the single parameter in the mean-shift based algorithm supports hierarchical clustering naturally.
在本文中，我们基于均值漂移算法，从扩散张量磁共振成像（DT-MRI）中提出了一种半自动丘脑和丘脑核分割算法。与现有的主要基于K均值算法的丘脑分割算法相比，我们基于均值漂移的算法更加灵活且具有适应性。它不假设高斯分布或固定数量的聚类。此外，基于均值漂移的算法中的单一参数自然地支持层次聚类。
