Thalamus segmentation from diffusion tensor magnetic resonance imaging.
Thalamus segmentation from diffusion tensor magnetic resonance imaging.
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DOI：
10.1155/2007/90216
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发表时间：
2007
影响因子：
7.6
通讯作者：
Xi, Yongjian
中科院分区：
文献类型：
--
作者：
Duan, Ye;Li, Xiaoling;Xi, Yongjian
提出了一种基于均值漂移算法的半自动扩散张量磁共振成像（DT-MRI）丘脑和丘脑核团分割算法。与现有的以K-means算法为主的丘脑分割算法相比，本文提出的基于均值漂移的丘脑分割算法具有更好的灵活性和自适应性。它不假设高斯分布或固定数量的集群。此外，基于均值漂移的算法中的单个参数自然地支持层次聚类。
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.