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首页> 外文会议>Annual International Conference of the IEEE Engineering in Medicine and Biology Society >Automatic segmentation of short association bundles using a new multi-subject atlas of the left hemisphere fronto-parietal brain connections
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Automatic segmentation of short association bundles using a new multi-subject atlas of the left hemisphere fronto-parietal brain connections

机译：使用新的左半球额顶大脑连接多主题图集对短缔合束进行自动分割

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Human brain connection map is far from being complete. In particular the study of the superficial white matter (SWM) is an unachieved task. Its description is essential for the understanding of human brain function and the study of the pathogenesis associated to it. In this work we developed a method for the automatic creation of a SWM bundle multi-subject atlas. The atlas generation method is based on a cortical parcellation for the extraction of fibers connecting two different gyri. Then, an intra-subject fiber clustering is applied, in order to divide each bundle into sub-bundles with similar shape. After that, a two-step inter-subject fiber clustering is used in order to find the correspondence between the sub-bundles across the subjects, fuse similar clusters and discard the outliers. The method was applied to 40 subjects of a high quality HARDI database, focused on the left hemisphere fronto-parietal and insula brain regions. We obtained an atlas composed of 44 bundles connecting 22 pair of ROIs. Then the atlas was used to automatically segment 39 new subjects from the database.
机译：人脑连接图还远远不够完整。特别地，浅表白质（SWM）的研究是一项未完成的任务。它的描述对于理解人脑功能以及与其相关的发病机制至关重要。在这项工作中，我们开发了一种自动创建SWM捆绑包多主题地图集的方法。地图集的生成方法基于皮质细胞分裂，用于提取连接两个不同回旋的纤维。然后，为了将每个束分成形状相似的子束，应用了一个组内的纤维簇。之后，使用两步主体间光纤聚类，以找到跨对象的子束之间的对应关系，融合相似的聚类并丢弃异常值。该方法已应用于40个高质量HARDI数据库的对象，重点放在左半球额顶和脑岛区域。我们获得了由连接22对ROI的44个束组成的图集。然后使用地图集自动从数据库中分割39个新主题。

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