Automated Hierarchical Clustering of DTI White Matter Fiber Tracts

Zhenyu Zhou¹, Yijun Liu², Guang Cao¹, Karen M. von Deneen², Dongrong Xu³

Recently, the tract-based analysis of white matter fibers has raised interests from the neurology and clinical neuroscience community since this methodology provides quantitative analysis of the properties of the specific fiber bundles, which provide a useful abstraction of the white matter structures and a clear identification of neural fibers. In order to benefit from the tract-based analysis, many clustering algorithms of the fiber tracts have been proposed. However, most approaches require a user initialization. In this paper, we propose a novel cluster method to automatically group brain white matter fibers into biologically meaningful neural tracts.