交互式轨迹图分割的快速聚类

E. Olivetti, Thien Bao Nguyen, E. Garyfallidis, Nivedita Agarwal, P. Avesani
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引用次数: 11

摘要

我们开发了一种新的交互式系统,用于人脑束状图分割,以帮助神经解剖学家从扩散磁共振成像(dMRI)数据中识别感兴趣的白质解剖结构。神经束图分割和导航的困难在于重建的神经元通路数量非常大,即流线,用现代dMRI技术可以达到数十万个数量级。我们系统的新颖之处在于向用户展示了一个束状图的聚类版本,用户可以在其中选择一些簇来识别感兴趣的流线的超集。然后以更小的规模重新聚集这个超集,并再次要求用户选择相关的集群。重复重新聚类和人工选择的过程,直到剩余的流线忠实地代表感兴趣的所需解剖结构。在此工作中,我们提出了一种解决大量流线在交互使用所要求的严格时间限制下聚类计算问题的解决方案。解决方案包括将流线嵌入欧几里得空间,然后采用最先进的k-means算法的可扩展实现。我们在肌萎缩性侧索硬化症(ALS)患者和健康受试者的束束造影上测试了该系统,我们收集了这些受试者用于即将进行的关于他们皮质脊髓束系统差异的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast Clustering for Interactive Tractography Segmentation
We developed a novel interactive system for human brain tractography segmentation to assist neuroanatomists in identifying white matter anatomical structures of interest from diffusion magnetic resonance imaging (dMRI) data. The difficulty in segmenting and navigating tractographies lies in the very large number of reconstructed neuronal pathways, i.e. the streamlines, which are in the order of hundreds of thousands with modern dMRI techniques. The novelty of our system resides in presenting the user a clustered version of the tractography in which she selects some of the clusters to identify a superset of the streamlines of interest. This superset is then re-clustered at a finer scale and again the user is requested to select the relevant clusters. The process of re-clustering and manual selection is iterated until the remaining streamlines faithfully represent the desired anatomical structure of interest. In this work we present a solution to solve the computational issue of clustering a large number of streamlines under the strict time constraints requested by the interactive use. The solution consists in embedding the streamlines into a Euclidean space and then in adopting a state-of-the art scalable implementation of the k-means algorithm. We tested the proposed system on tractographies from amyotrophic lateral sclerosis (ALS) patients and healthy subjects that we collected for a forthcoming study about the systematic differences between their corticospinal tracts.
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